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machine learning engineer

The Home Depot

<div><div><p><b>Position Purpose:</b></p><p>
The Staff Software Engineer is responsible for leading a team of engineers building and designing a product that our customers and associates love. As a Staff Software Engineer, you will be part of a dynamic team with engineers of all experience levels who help each other build and grow technical and leadership skills while creating, deploying, and supporting production applications. In this role, you will also provide technical leadership on machine learning systems, including model development, production deployment, monitoring, and lifecycle management of ML solutions operating at scale. In addition, Staff Software Engineers will assist in product and tool selection, configuration, security, resilience, performance tuning and production monitoring.</p><p><br>
Staff Software Engineers contribute to foundational code elements that can be reused as well as architectural diagrams and other product-related documentation. You will help define best practices for building reliable, explainable, and maintainable ML systems that integrate seamlessly with broader software platforms.</p><p><br>
As a Staff Software Engineer, you will be a core player on the product team and are expected to build and grow the skillsets of the more junior Engineers.</p><p><b><br>
Key Responsibilities:</b></p><ul><li>
45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate</li><li>
20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul><p><b><br>
Direct Manager/Direct Reports:</b></p><ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul><p><b><br>
Travel Requirements:</b></p><ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul><p><b><br>
Physical Requirements:</b></p><ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul><p><b><br>
Working Conditions:</b></p><ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul><p><b><br>
Minimum Qualifications:</b></p><ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul><p><b><br>
Preferred Qualifications:</b></p><ul><li>
3 - 6 years of relevant work experience</li><li>
Strong experience designing, training, evaluating, and deploying machine learning models in production environments, including batch and real-time inference systems</li><li>
Experience with ML lifecycle management, including feature engineering, model versioning, experimentation, validation, and monitoring for data drift and model performance degradation</li><li>
Experience building and operating ML pipelines using cloud-native services, data platforms, and CI/CD practices for reproducible and reliable model deployment</li><li>
Strong understanding of applied statistics, model evaluation metrics, and tradeoffs between model accuracy, interpretability, latency, and operational cost</li><li>
Experience with algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Experience in training machine learning models with extremely large datasets</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc. - and experience integrating them into scalable software systems</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in version control systems (preferable Git)</li><li>
Experience in a Linux or Unix based environment</li><li>
Experience in a CI/CD toolchain</li><li>
Experience in REST and effective web service design</li><li>
Experience in production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Experience in cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Experience in defensive coding practices and patterns for high Availability</li><li>
Experience in A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer</li></ul><p><b><br>
Minimum Education:</b></p><ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul><p><b><br>
Preferred Education:</b></p><ul><li>
No additional education</li></ul><p><b><br>
Minimum Years of Work Experience:</b></p><ul><li>
3</li></ul><p><b><br>
Preferred Years of Work Experience:</b></p><ul><li>
No additional years of experience</li></ul><p><b><br>
Minimum Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Preferred Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Certifications:</b></p><ul><li>
None</li></ul><p><b><br>
Competencies:</b></p><ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul></div><p></p><p><br>
Apply End Date: 04/01/2026</p></div>

Staff Machine Learning Engineer

Metas Solutions

<div><p><b>Metas Solutions</b> has an <b>&quot;</b><b><i>opening&quot;</i></b> for a talented <b>Senior Data Engineer </b>based in <b>Atlanta</b>,<b> GA</b>. The ideal candidate must be able to work onsite in the Atlanta metro area and someone who's proficient in Databricks workspaces and Azure infrastructure. In this position, you'll drive the next generation of our analytics products by architecting and delivering end-to-end cloud analytics solutions. In a fully cloud-native environment, you'll partner with product managers, data scientists, software engineers, machine learning (ML) engineers and business analysts to enable and support a platform that powers personalized experiences and operational efficiency. You'll leverage automated model CI/CD, containerized deployments (Docker/Kubernetes), and real-time monitoring to ensure our ML systems are reliable, secure, and scalable.</p><p>
You will be responsible for the design, implementation, and maintenance of the Databricks workspaces and its associated Azure infrastructure. You will manage and optimize data and machine learning workloads, ensuring a reliable, secure, and scalable platform for business analysts, data engineering and data science teams.</p><p><b>
Responsibilities:</b></p><ul><li>
Lead the administration and governance framework of the platform regarding the security posture of the enterprise and its key stakeholders</li><li>
Design and implement automated solutions to streamline accounts and workspace administration</li><li>
Collaborate with cross-functional teams to understand business needs and translate them into ML solutions</li><li>
Mentor junior engineers and provide technical leadership in Databricks best practices and techniques</li><li>
Conduct cost and performance analysis of the various computes, and data assets within the platform</li><li>
Stay current with the latest advancements in Databricks SQL, Machine Learning and AI, and integrate new technologies and methods as applicable</li><li>
Engage in knowledge sharing and contribute to building a strong, collaborative team environment</li></ul><p><b>
Qualifications:</b></p><ul><li>
5+ years of experience with Databricks Account and Workspace Administration, including governance, configuration, and security management</li><li>
Experience with optimizing Databricks environments for cost efficiency, performance, and reliability</li><li>
Experience with developing and maintaining Databricks data pipelines using Autoloader, Delta Live Tables, and Databricks Workflows</li><li>
Experience with implementing MLOps solutions using MLflow 2.0/3.0, Serving Endpoints, and Model Registry in production environments</li><li>
Experience with Databricks SQL tools such as Queries and AI/BI Dashboards</li><li>
Experience with large datasets and distributed computing across cloud platforms (AWS, GCP, Azure), including Azure services like Entra ID, Data Factory, Key Vault, and Purview</li><li>
Knowledge of Unity Catalog Governance Architecture and enterprise data security best practices</li><li>
Possession of strong communication and documentation skills with the ability to clearly convey complex technical concepts to both technical and non-technical audiences</li><li>
Ability to work on-site in Atlanta, Georgia</li><li>
Master's degree in computer science, Computer Engineering, or related programs</li></ul><p><b>
Additional Qualifications:</b></p><ul><li>
Knowledge of Azure Cloud Networking concepts like VNET Injection</li><li>
Databricks Platform Administrator Certification</li><li>
Microsoft Certified: Azure Administrator Associate</li></ul><p><b>
Security Requirements:</b></p><ul><li>
Must be US Citizen and with the ability to obtain a US Government security clearance (Public Trust 5) within a reasonable period</li><li>
Market competitive salary, commensurate with experience and education</li><li>
Comprehensive benefits package available, Medical, Dental, Vision and Life Insurance, Paid Time Off (PTO), 401K with company match, growth, and promotion opportunities</li></ul><p>
</p><p><b><i>We are an Equal Opportunity Employer/Veterans/Disabled</i></b></p></div>

Senior Data Engineer

<div><p><b>Position Purpose:</b></p><p>
We are transforming how merchandising decisions are made through AI-powered solutions and automation. This Sr. Data Scientist plays a key role to build scalable, mathematical algorithms in production that directly impact retail and merchandising by solving complex, high-value business problems. The position focuses on science-driven models, operating at the intersection of data science, process automation, cloud deployment, and software production to deliver reliable decision systems that increase efficiency and improve customer experience.</p><p>
This role leads Machine Learning initiatives end-to-end, from cross-functional collaboration and business problem framing through technical design, development, deployment, and ongoing monitoring and enhancement. The Sr. Data Scientist partners closely with product managers, software engineers, and business stakeholders to identify high-impact opportunities, translate into technical requirements, and deliver scalable solutions in production. The role is responsible for communicating insights and recommendations to both technical and non-technical audiences, mentoring data scientists on projects, and ensuring models perform effectively based on real-world outcomes.</p><p><b><br>
Key Responsibilities:</b></p><ul><li>
35% Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation</li><li>
30% Project Management &amp; Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team</li><li>
20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage</li><li>
15% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Define best practices and develop clear vision for data analysis and model productionalization; Contribute to library of reusable algorithms for future use, ensuring developed codes are documented</li></ul><p><b><br>
Direct Manager/Direct Reports:</b></p><ul><li>
This position reports to manager or above</li><li>
This position has 0 Direct Reports</li></ul><p><b><br>
Travel Requirements:</b></p><ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul><p><b><br>
Physical Requirements:</b></p><ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul><p><b><br>
Working Conditions:</b></p><ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul><p><b><br>
Minimum Qualifications:</b></p><ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul><p><b><br>
Preferred Qualifications:</b></p><ul><li>
Master&rsquo;s or PhD in Data Science, Statistics, Economics, Applied Math, Engineering, or other quantitative and engineering fields.</li><li>
6+ years of hands-on experience developing and deploying Machine Learning models into production environments and integrating into scalable data pipelines and decision systems (e.g., via APIs, microservices, or batch pipelines), ensuring reliability, scalability, traceability, and interoperability.</li><li>
Deep expertise in causal inference (e.g., Difference-in-Differences, Double ML, Synthetic Control) and discrete choice models, including elasticity, substitution and demand transfer.</li><li>
Solid foundation in machine learning models (e.g., regularized regression, tree-based methods such as XGBoost, and neural networks)</li><li>
Strong experience with forecasting models (e.g., time-series forecasting. ARIMA, Bayesian and probabilistic methods or deep learning-based approaches).</li><li>
Strong understanding of data structures, and modern cloud ecosystems (GCP, AWS, etc.).</li><li>
Proficient with data visualization software (preferably Tableau).</li><li>
Familiarity with GenAI, LLM and Agentic framework, with experience integrating LLM-based reasoning into ML-driven solutions.</li><li>
Comfortable collaborating with front-end developers or building light UI prototypes (e.g., Streamlit, React).</li><li>
Demonstrated strength in business communication and technical leadership, with the ability to clearly explain complex statistical and ML concepts to non-technical stakeholders in a way that builds trust and drives adoption.</li><li>
Experience solving retail or merchandising problems such as assortment &amp; space optimization, demand transfer, consumer choice models, demand forecasting.</li></ul><p><b><br>
Minimum Education:</b></p><ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul><p><b><br>
Preferred Education:</b></p><ul><li>
No additional education</li></ul><p><b><br>
Minimum Years of Work Experience:</b></p><ul><li>
5</li></ul><p><b><br>
Preferred Years of Work Experience:</b></p><ul><li>
No additional years of experience</li></ul><p><b><br>
Minimum Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Preferred Leadership Experience:</b></p><ul><li>
None</li></ul><p><b><br>
Certifications:</b></p><ul><li>
None</li></ul><p><b><br>
Competencies:</b></p><ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Cultivates Innovation: Creating new and better ways for the organization to be successful</li><li>
Customer Focus: Building strong customer relationships and delivering customer-centric solutions</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Results: Consistently achieving results, even under tough circumstances</li><li>
Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder</li><li>
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement</li><li>
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels</li></ul></div><p></p>

Sr Data Scientist- Assortment and Space Planning (Core ML)

Sequium Asset Solutions

<div><p>Job title: Entry Level Data Scientist - Collections Analytics</p><p>
Location: Atlanta, GA or Remote</p><p>
Employment type: Full-time</p><p>
Reports to: VP Strategic Initiatives</p><p><b>
About us</b></p><p>
Sequium Asset Solutions is the industry's most progressive and advanced debt collection servicer. Our mission is to provide uncompromising operational excellence by setting the highest standards in service and reliability through the application of our five core values: Leadership, Training, Talent Acquisition, Rewards and Technology. At Sequium, <b>Tomorrow is Today.</b></p><p>
We have an outstanding opportunity for an accomplished data scientist to join one of the most exciting and fastest growing companies in the industry. In this role you will report directly to the Vice President of Strategic Initiatives and support analytics and modeling projects across account segmentation, contact strategy optimization, and early-warning</p><p>
detection. You will work with cross-functional teams (operations, compliance, IT) to turn data into actionable insights, build repeatable analytics, and productionize models. Our company has made huge investments in data science and generated an agentic AI. We are attempting to fully automate all decisioning processes to give us the highest statistical result and incremental value for all performance matrices.</p><p>
The successful applicant must possess a high level of intelligence, motivation and enthusiasm in creating breakthrough value enhancements. This is a critical position within the organization for someone who is creative, self-starting and who wants to be in control of their own destiny.</p><p><b>
Key responsibilities</b></p><ul><li>
Must have significant knowledge using enterprise AI software (Claude, Cursor and Python) with the ability to direct and prompt this software in order to create significant breakthroughs to enhance automated and real-time strategies.</li><li>
Build, validate, and maintain predictive models (e.g., credit/payment propensity, churn/risk, contact response) using Python/R and standard ML libraries.</li><li>
Clean, explore, and feature-engineer large-structured datasets from multiple sources (payments, contact history, credit bureau, CRM).</li><li>
Run A/B tests and propensity-matched experiments to evaluate contact strategies and messaging, measure lift and report results.</li><li>
Create dashboards, visualizations, and regular reports for operations and leadership (KPIs: recovery rates, promise-to-pay keep rates, contact conversion, roll rates).</li><li>
Assist in productionizing models: packaging, documentation, monitoring, and retraining schedules in collaboration with others.</li><li>
Implement and track model performance, fairness, and stability metrics; support model governance and compliance documentation.</li><li>
Support data pipelines and ETL tasks; partner with data engineering to ensure data quality and lineage.</li><li>
Translate business problems into analytical approaches; present findings and recommended actions to stakeholders.</li><li>
Stay current on best practices in supervised/unsupervised learning, causal inference, and responsible AI as applied to collections.</li></ul><p><b>
Required qualifications</b></p><ul><li>
Bachelor&rsquo;s degree (or equivalent) in Data Science, Statistics, Computer Science, Mathematics, Industrial Engineering, or related quantitative field; graduation within the last 2-3 years.</li><li>
Solid SQL skills for data extraction and manipulation.</li><li>
Strong programming skills in Python.</li><li>
Understanding of basic ML algorithms (logistic regression, decision trees, ensemble methods, clustering) and evaluation metrics (precision/recall, confusion matrix, calibration).</li><li>
Experience with data visualization tools (Power BI, Tableau or equivalent) or ability to produce clear visual analyses in Python/R.</li><li>
Hands-on experience with at least one machine learning project (class project, internship, capstone, or competition) with end-to-end work (data cleaning, modeling, evaluation).</li><li>
Strong analytical problem-solving, attention to detail, and ability to communicate technical results to non-technical stakeholders.</li><li>
Commitment to ethical data practices and regulatory compliance (willingness to learn collections/consumer protection rules).</li></ul><p><b>
Preferred (nice-to-have)</b></p><ul><li>
Internship or part-time experience in finance, collections, payments, credit risk, or customer analytics.</li><li>
Familiarity with time-series or survival analysis and propensity scoring.</li><li>
Experience with model monitoring frameworks, cloud platforms (AWS, GCP, Azure).</li><li>
Knowledge of compliance/regulatory frameworks relevant to collections (e.g., FDCPA basics).</li></ul><p><b>
Technical stack expectations</b></p><ul><li>
Data: SQL, relational databases</li><li>
Visualization: Power BI</li><li>
Languages: Python (R acceptable)</li><li>
ML: scikit-learn, XGBoost/LightGBM, basic knowledge of neural nets optional</li><li>
Workflow: Git, Jupyter notebooks, basic command line</li><li>
Cloud/Infrastructure: AWS/GCP/Azure; containerization (Docker), Kubernetes experience preferred</li></ul><p><b>
Success metrics (first 6&ndash;12 months)</b></p><ul><li>
Deliver at least one validated predictive model and support its production handoff</li><li>
Implement 2&ndash;3 dashboards or automated reports used by operations.</li><li>
Demonstrate measurable lift from an A/B test or strategy change driven by your analysis.</li><li>
Complete formal documentation for at least one model covering training data, features, performance, and monitoring plan.</li></ul><p><b>
Behavioral competencies</b></p><ul><li>
Curious, proactive learner who seeks feedback and owns development.</li><li>
Team player who collaborates with ops, IT, and compliance.</li><li>
Communicates clearly, distills complex analyses into actionable recommendations.</li><li>
Comfortable working in a regulated, data-sensitive environment.</li></ul><p><b>
Application process</b></p><p>
Submit resume, transcript (unofficial acceptable), and a one-page project summary showing relevant work.</p></div>

Entry Level Data Scientist - Collections Analytics

<div><p><b>Be part of something groundbreaking</b></p><p></p><p>
At AIG, we are making long-term investments in a brand-new, innovative Generative AI team, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond, and we need your help.
</p><p></p><p>With the support and investment needed to explore new frontiers in generative AI, you&rsquo;ll be working alongside talented colleagues, innovating and leading projects that will transform how we manage risk and serve our customers.
</p><p></p><p>This team is central to our vision of the future and the core of our business offering. We will incorporate best-in-class engineering and product management principles, and your guidance and collaboration will be critical to its success.</p><p></p><p>
To rapidly advance and innovate, we need your skills and expertise to build and scale world-class products. If you&rsquo;re excited by the opportunity to create meaningful impact, we&rsquo;d love to hear from you.</p><p></p><p><b>
Who we are</b></p><p></p><p>
AIG is a leading global insurance organization providing a wide range of property casualty insurance and other financial services. We provide world-class products and expertise to businesses and individuals in approximately 190 countries and jurisdictions.
</p><p></p><p>At AIG, we&rsquo;re reshaping how the world manages risk, and we&rsquo;re inviting you to be a key part of that transformation. As our Data Scientist you will have the opportunity to make a meaningful impact, leveraging and further developing your skills to guide groundbreaking AI initiatives. If you&rsquo;re looking for a place to grow your career and where your contributions will shape the future, AIG is where you belong.
</p><p></p><p><b>How you will create impact:</b></p><p></p><p>
This role is critical to innovation team in AICOE. Through this initiative, we are building a strategic capability to Implement Advanced AI Techniques, including RAG, Knowledge Graph, Agentic design, POC and Model Context Protocol MCP with evaluators to ensure reliability and performance. This role is critical to contribute to the invention in AIG GenAI&rsquo;s projects and AIG&rsquo;s Intelligent property, which keeps AIG leading the insurance industry in Gen AI area.</p><p></p><p><b>
Your responsibilities include:</b></p><ul><li><p>
GenAI research and application: Stay up to date with the latest advancements in GenAI and apply this knowledge to develop innovative solutions that drive member and business value. This includes designing and implementing novel architectures, algorithms, and techniques for LLMs, multi-modal models, and other GenAI applications. Be accountable for high-quality data science solutions with respect to accuracy, coverage, scalability, stability, and business adoption</p></li><li><p>
Agentic system development and optimization: Design and build enterprise level Agentic solution, including data processing and curation, to mitigate biases and ensure high-quality datasets for optimized model performance. Influence efficient Agentic architecture design for optimal performance, efficiency, and scalability</p></li><li><p>
Research strategy and direction: Define and drive the long-term research vision and strategy for GenAI in the organization, aligning with business objectives and goals. This includes identifying key research areas, setting ambitious goals, and developing achievable milestones. Take ownership of algorithms and drive enhancements/optimizations based on business requirements with proper documentation and code-reusability</p></li><li><p>
Collaboration and communication: Effectively collaborate with and communicate complex research concepts to cross-functional teams, including engineering, product, and business stakeholders. This includes distilling research findings into actionable insights, providing technical guidance, and influencing the adoption of GenAI solutions</p></li><li><p>
GenAI thought leader: Advance expertise in GenAI through continuous learning, attending conferences, and engaging with the broader research community. Contribute to the team's knowledge base and advance the field through publications, presentations, and sharing of insights and expertise</p></li></ul><p></p><p><b>
What is needed to be successful:</b></p><ul><li><p>
Ph.D. with 2+ years&rsquo; industry experience</p></li><li><p>
Design and deploy Agentic AI solutions to automate complex business workflows, enhance decision-making, and improve customer and employee experiences.</p></li><li><p>
Translate research in agentic AI, reinforcement learning, and reasoning into practical solutions that support underwriting, Operation, claims automation, customer servicing, and risk assessment</p></li><li><p>
Experience implementing Agentic AI frameworks, such as CrewAI, Claude Agent sdk and LangChain, to build autonomous systems in production settings</p></li><li><p>
Strong ML, Deep Learning and Gen AI hand-on and scientific research skills</p></li><li><p>
Have produced novel research related to agentic design and implementation</p></li><li><p>
Experience in designing and implementing Model Context Protocol (MCP) servers to enable seamless integration between AI agents, enterprise systems, and external tools</p></li><li><p>
Specialized expertise in other topics like fine-tuning, RLHF, RAG and Knowledge graph etc.</p></li><li><p>
Experience in designing and implementing Model Context Protocol (MCP) servers to enable seamless integration between AI agents, enterprise systems, and external tools</p></li><li><p>
Knowledge of Palantir platforms will be plus</p></li><li><p>
Ph.D. Publication with GenAI and/or Agentic is a plus</p></li><li><p>
Are passionate about getting your work into the hands of real users and - more broadly - democratizing access to modern AI technology.</p></li><li><p>
Are motivated by working on Gen AI research that - contrary to the general trend in the field - will be disclosed to the public.</p></li><li><p>
Strong communication skills and a desire to work on a small, fast-paced team</p></li></ul><p></p><p>
Veterans are encouraged to apply.</p><p><br>
#LI-RG2 #LI-AIG #AI #GenAI #artificialintelligence #DataScience #BigData</p><p></p><p>
At AIG, we value in-person collaboration as a vital part of our culture, which is why we ask our team members to be primarily in the office. This approach helps us work together effectively and create a supportive, connected environment for our team and clients alike.</p><p></p><p><b>
Enjoy benefits that take care of what matters</b></p><p>
At AIG, our people are our greatest asset. We know how important it is to protect and invest in what&rsquo;s most important to you. That is why we created our Total Rewards Program, a comprehensive benefits package that extends beyond time spent at work to offer benefits focused on your health, wellbeing and financial security&mdash;as well as your professional development&mdash;to bring peace of mind to you and your family.</p><p></p><p><b>
Reimagining insurance to make a bigger difference to the world</b></p><p>
American International Group, Inc. (AIG) is a global leader in commercial and personal insurance solutions; we are one of the world&rsquo;s most far-reaching property casualty networks. It is an exciting time to join us &mdash; across our operations, we are thinking in new and innovative ways to deliver ever-better solutions to our customers. At AIG, you can go further to support individuals, businesses, and communities, helping them to manage risk, respond to times of uncertainty and discover new potential. We invest in our largest asset, our people, through continuous learning and development, in a culture that celebrates everyone for who they are and what they want to become.</p><p></p><p><b>
Welcome to a culture of </b><b>inclusion</b></p><p>
We&rsquo;re committed to creating a culture that truly respects and celebrates each other&rsquo;s talents, backgrounds, cultures, opinions and goals. We foster a culture of inclusion and belonging through learning, cultural awareness activities and Employee Resource Groups (ERGs). With global chapters, ERGs are a cornerstone for our culture of inclusion. The talent of our people is one of AIG&rsquo;s greatest assets, and we are honored that our drive for positive change has been recognized by numerous recent awards and accreditations.</p><p></p><p><i>
AIG provides equal opportunity to all qualified individuals regardless of race, color, religion, age, gender, gender expression, national origin, veteran status, disability or any other legally protected categories.</i></p><p></p><p>
AIG is committed to working with and providing reasonable accommodations to job applicants and employees with disabilities. If you believe you need a reasonable accommodation, please send an email to candidatecare@aig.com.
</p><p></p><div><div><div><div><div><div><div><p>Functional Area:</p></div></div></div></div></div></div></div>
DT - Data<p></p>
AIG PC Global Services, Inc.</div><p></p>

Ph.D. Research Data Scientist, GenAI

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you passionate about Generative AI (GenAI)? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help some of our largest customers build and deploy GenAI enabled applications using Amazon Bedrock and SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.<br>
<br>
At Amazon, we&rsquo;ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com&rsquo;s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it&rsquo;s a big part of our heritage.<br>
<br>
AWS is looking for a Generative AI Solutions Architect who will be the Subject Matter Expert (SME) for helping customers in designing solutions that leverage our Generative AI services. You will interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI. As part of the Generative AI Worldwide Specialist organization, you will work closely with other Solution Architects from various geographies to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI services. You will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review.
<br>
<br>
You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. You must have experience with embedding model fine tuning and retrieval method evaluation approaches. You should understand the security and compliance requirements for ML/GenAI implementations. You must have experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, and Performance Evaluation frameworks. You should have experience architecting end to end ML/Gen AI applications for customers using AWS services and Well Architected Framework.<br>
<br>
Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation.<br>
<br>
Travel up to 50% may be possible.<br>
<br>
Key job responsibilities<br>
- Customer Advisor- Implement, and deploy state of the art machine learning solutins under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers.<br>
<ul><li>Thought Leadership &ndash; Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
</li><li>Partner with Data Scientists, SAs, Sales, Business Development and the Generative AI Service teams to accelerate customer adoption and providing guidance on their customer engagements.
</li><li>Act as a technical liaison between customers and the AWS Generative AI services teams to provide customer driven product improvement feedback.
</li><li>Develop and support an AWS internal community of GenAI related subject matter experts worldwide. Create field enablement materials for the broader technical population, to help them understand how to integrate AWS GenAI solutions into customer architectures.
</li></ul><br>
About the team<br>
Diverse Experiences<br>
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
<br>
Why AWS?<br>
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.<br>
Inclusive Team Culture<br>
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.<br>
Mentorship &amp; Career Growth<br>
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
<br>
Work/Life Balance<br>
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve.</div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>7+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data &amp; analytics) experience</li><li>3+ years of design, implementation, or consulting in applications and infrastructures experience</li><li>7+ years of IT development or implementation/consulting in the software or Internet industries experience</li><li>Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience working with PyTorch or JAX software</li><li>3+ years of experience in end to end technical architecture, design, deployment and operations for Generative AI/ML platforms and applications.</li><li>Proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches.&quot;</li><li>Proficient with prompt engineering, function calling, agentic workflows, embedding model fine tuning and retrieval method evaluation and optimization approaches.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>5+ years of infrastructure architecture, database architecture and networking experience</li><li>Experience working with end user or developer communities</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, CA, Mountain View - 176,600.00 - 239,000.00 USD annually<br>
USA, CA, San Francisco - 176,600.00 - 239,000.00 USD annually<br>
USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually<br>
USA, NJ, Jersey City - 169,000.00 - 228,600.00 USD annually<br>
USA, NY, New York - 169,000.00 - 228,600.00 USD annually<br>
USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually<br>
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually</div><p></p>

Senior Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM

Delta Air Lines

<div></div><div><div><div><div><div><div><b>UNITED STATES, GEORGIA, ATLANTA</b></div><b><br>
 </b><div></div><div><b>RESERVATIONS &amp; CUST. CARE</b></div><b><br>
 </b><div></div><div><b>02-MAR-2026</b></div><b><br>
 </b><div></div><div><b>REF #: 30956</b></div><b>
</b></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>HOW YOU'LL HELP US KEEP CLIMBING (OVERVIEW &amp; KEY RESPONSIBILITIES)</b></h3>
</div></div><div><div><div><b>oin Delta Air Lines as a Reservations Intern and help shape the future of customer care</b>. You&rsquo;ll work on high-impact projects that improve the servicing experiences for millions of customers while gaining hands-on experience in data analytics, process improvement, product management, or statistical modeling. While interning in Reservations you&rsquo;ll gain:</div><div>
Real-world experience in a Fortune 100 company</div><div>
Experience presenting to an executive audience</div><div>
Mentorship and networking opportunities</div><div></div><div><b><br>
What is Reservations?</b></div><div>
As a department, Reservations serves as the point of contact for our customers before, during, and after travel. This internship is a back-office role at our General Offices (GO), where you&rsquo;ll support our Customer Engagement Centers by providing essential behind-the-scenes assistance that helps improve the experience of both the Delta customer and the agents who serve them.</div><div></div><div><b><br>
Job Summary:</b></div><div>
The Reservations Intern serves as an internal consultant, leading semester-long projects that support divisional strategies and goals. These initiatives often involve cross-functional collaboration to identify opportunities and recommend solutions that enhance both customer and specialist experiences.</div><div></div><div><b><br>
What are we looking for?</b></div><div>
An ideal candidate will have educational experience in machine learning, statistical analysis, and data storytelling. The candidate should have good organizational and communication skills and feel comfortable in a fast-paced environment.</div><div></div><div><br>
Primary functions of the graduate-level intern include:</div><div><ul><li>
Partnering with existing data scientists to develop advanced analytics solutions for complex business problems</li><li>
Collecting data via SQL/Python queries and performing exploratory data analysis</li><li>
Presenting analysis to business partners in a digestible way</li></ul></div><div></div><div><br>
These large and complex projects may contain highly confidential material and present moderate financial risk. The final project deliverable is a capstone presentation given to division leaders highlighting project lessons learned, impacts made, and recommendations going forward.</div></div>
</div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>WHAT YOU NEED TO SUCCEED (MINIMUM QUALIFICATIONS)</b></h3>
</div></div><div><div><div><ul><li>Must be currently pursuing a Doctor of Philosophy degree</li><li>
Not enrolled in any classes (remote or on-campus) during the duration of the program</li><li>
Must be able to work 16 consecutive weeks</li><li>
Must be willing to travel as required</li><li>
Must be able to come into Corporate Headquarters in Atlanta 2 &ndash; 3 times a week</li><li>
A strong team player, detail oriented, and perform well under pressure</li><li>
Conveys professional image to all levels of associates</li></ul></div><div></div><div><br>
Proficient in tools such as:</div><div><ul><li>
Classic Machine Learning Models</li><li>
SQL</li><li>
Python</li><li>
Experience with pandas, scikit-learn, or similar libraries</li><li>
Git</li></ul></div></div><ul><li><i>
Consistently prioritizes safety and security of self, others, and personal data.</i></li><li><i>
Embraces diverse people, thinking, and styles.</i></li><li><i>
Possesses a high school diploma, GED, or high school equivalency.</i></li><li><i>
Is at least 18 years of age and has authorization to work in the United States.</i></li></ul>
</div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>WHAT WILL GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS)</b></h3>
</div></div><div><div><div><div><ul><li>Experience in previous corporate environments in part-time or full-time capacity</li><li>
Strong written and verbal communication skills highly preferred</li></ul></div><div>
Experience with:</div><div><ul><li>
Relational and non-relational databases</li><li>
Data types (structured, unstructured, log, audio recordings, images, etc.)</li><li>
Simulation in python</li><li>
Dbt and other SQL orchestration tools</li><li>
AWS experience</li><li>
Data visualization tool knowledge (Power BI, Tableau, etc.)</li></ul></div><div>
Delta Air Lines recognizes and values diversity. We are an equal opportunity employer.</div></div></div></div></div></div></div><p></p>

Ph.D. Intern, Reservations (Data Science) - Summer 2026

Explore 59+ Machine learning engineer in Atlanta this March. Find roles across top companies and apply now to boost your career.