business teacher (postsecondary – ai training)

senior data engineer

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business teacher (postsecondary – ai training) Jobs in Atlanta

civil engineer iii

ai engineer

Powerplan

<div>Overview:

The Senior AI/ML Engineer will modernize and scale the company&rsquo;s enterprise data and AI platform by designing AI-ready data models, operationalizing ML systems, and enabling natural-language analytics through Databricks Genie or equivalent AI tooling.
This role exists to shift the organization from dashboard-driven analytics to AI-powered decision intelligence at enterprise scale.
Responsibilities:

Performance Objectives 
Modernize and Operationalize the Analytics Data Platform
Within 6&ndash;9 months, design and implement a scalable medallion-based architecture (Bronze/Silver/Gold) in Databricks or Snowflake that supports AI-ready datasets, improves query performance by 30%, and reduces data reliability incidents by 40%.
Subtasks:<ul><li>
Redesign analytical data models for AI/ML consumption</li><li>
Implement governance using Unity Catalog or Snowflake controls</li><li>
Optimize distributed compute performance</li><li>
Establish monitoring and quality validation checkpoints</li></ul> 
Enable AI-Ready Data Modeling &amp; Governance
Within 6 months, establish semantic models and metadata standards that enable business-facing AI querying with 95% data trust rating from stakeholders.
Subtasks:<ul><li>
Standardize schema design for ML and GenAI workloads</li><li>
Align business definitions with governed datasets</li><li>
Implement lineage and access controls</li><li>
Reduce duplicate or conflicting metric definitions</li></ul> 
Build and Deploy Production-Grade ML Pipelines
Within 9&ndash;12 months, implement reusable ML lifecycle pipelines (experimentation training evaluation deployment) that reduce time-to-production for ML models by 50%.
Subtasks:<ul><li>
Standardize MLflow/Feature Store workflows</li><li>
Implement CI/CD for ML</li><li>
Improve model observability and drift monitoring</li><li>
Establish model documentation standards</li></ul> 
Implement Natural Language AI Analytics (Databricks Genie Enablement)
Within 6 months, deploy and optimize Databricks Genie (or equivalent AI query interface) enabling business users to generate accurate plain-language insights with 80% adoption across target user groups.
Subtasks:<ul><li>
Translate business questions into semantic AI-ready datasets</li><li>
Improve response accuracy through model + metadata tuning</li><li>
Partner with Product on use-case prioritization</li><li>
Track and improve AI query accuracy and user engagement</li></ul> 
Democratize AI Across Business Teams
Within 12 months, embed AI-driven analytics into at least 3 core business workflows, demonstrating measurable business impact (e.g., cost reduction, revenue lift, or decision cycle time improvement).
Subtasks:<ul><li>
Identify high-value AI use cases</li><li>
Collaborate cross-functionally</li><li>
Deliver production-ready AI solutions</li><li>
Document business ROI outcomes</li></ul> 
Establish Enterprise AI Platform Standards
Within 12 months, define and institutionalize architectural standards, best practices, and governance frameworks adopted across Engineering and Analytics teams.
Subtasks:<ul><li>
Publish architecture reference patterns</li><li>
Lead design reviews</li><li>
Mentor engineers</li><li>
Influence long-term AI strategy</li></ul> 
Success Metrics Summary<ul><li>
30%+ performance improvement in analytics workloads</li><li>
40%+ reduction in data quality incidents</li><li>
50% reduction in ML deployment cycle time</li><li>
80% Genie adoption in target group</li><li>
3+ AI use cases with measurable ROI</li><li><ul><li>95% stakeholder trust in AI-generated insights</li></ul></li></ul>
Qualifications:

Growth &amp; Career Move
This is a high-impact platform leadership role enabling enterprise AI transformation. The individual will shape architecture standards, influence executive AI strategy, and lead the shift from traditional BI to AI-powered decision intelligence.
Required Qualifications<ul><li>
10+ years of experience in Data Analytics, Data Engineering, ML Engineering, or AI Engineering</li><li>
Strong hands-on experience with Databricks or Snowflake in production environments</li><li>
Expertise in SQL, Python, and distributed data processing (Spark preferred)</li><li>
Strong understanding of data modeling for analytics and AI</li><li>
Experience building and deploying ML models in real-world systems</li><li>
Familiarity with LLMs, GenAI concepts, and AI-assisted analytics</li><li>
Experience with ML lifecycle tools (MLflow, Feature Stores, CI/CD for ML)</li></ul><div></div><div> 
Preferred Qualifications</div><ul><li>
Direct experience with Databricks Genie or AI-powered BI tools</li><li>
Experience with Unity Catalog, Delta Live Tables, or Snowflake governance features</li><li>
Exposure to Azure, AWS, or GCP cloud platforms</li><li>
Experience working in regulated or enterprise SaaS environments</li><li>
Ability to explain complex technical concepts to non-technical stakeholders</li></ul><div></div><div> 
What Success Looks Like in This Role</div><ul><li>
Business users can ask questions in plain English and get trusted, accurate insights</li><li>
Data models are AI-ready, scalable, and well-governed</li><li>
ML models move smoothly from experimentation to production</li><li>
Databricks Genie adoption grows with measurable business impact</li><li>
AI is embedded into analytics not bolted on</li></ul><div></div><div> 
Why Join Us</div><ul><li>
Work on real AI/ML problems at enterprise scale</li><li>
Influence the evolution of a modern data + AI platform</li><li>
Partner with senior leaders shaping the company&rsquo;s AI-first future</li><li>
Build systems that turn data into decisions not dashboards</li></ul><div>
PowerPlan is an EOE</div><div>
Applicant Privacy Notice</div><div></div> 
Please note that this is a hybrid role that involves a combination of onsite work from our corporate office as well as work from home. While we strive to accommodate flexible working arrangements when sensible, there will be times when onsite work is required. This could include scheduled office days, team meetings, client meetings, or special events.</div>

Senior Databricks AI Engineer

Rev.io

<div>About Rev.io

Rev.io provides configurable software for billing, customer management, business management, payments, analytics, provisioning, and automation to service providers in telecommunications, Wireless &amp; IoT, managed IT services, A/V, security integration, and other related industries. Our modern, cloud-based software delivers the industry&rsquo;s most complete quote-to-cash experience, enabling our clients to grow their revenue efficiently.

Rev.io is an Atlanta-based company with offices in Atlanta and West Virginia. We have more than 21 years in business serving our clients. While we are very experienced in what we do, we are still growing rapidly, and we are looking for exceptional people who are excited to join us on a career-defining journey.

In all of our daily work, each of us is guided by our mission, vision and &ldquo;ACT TOP&rdquo; values.

Our Mission: To help clients grow revenue efficiently.

Our Vision: To be the best billing &amp; back-office software company in the world by providing innovative solutions and extraordinary service to our clients and end users.

Our ACT TOP Values:
<ul><li>
Achieving Extraordinary Results: Doing more than expected and pursuing a higher standard of work without compromising your job responsibilities.</li><li>
Caring For Employees, Clients and Community: Demonstrating empathy and concern by helping those who are most in need.</li><li>
Take Responsibility and Act Like An Owner: Being accountable and doing the right thing even when no one is watching.</li><li>
Transparent Leadership: Communicating openly, regardless of title or situation.</li><li>
Opportunity To Make a Positive Difference: Recognizing situations and taking action to produce a better outcome.</li><li>
Passion For Innovation: Enthusiastically finding new solutions to improve efficiency.
</li></ul>In a recent national survey, 97% of our employees agreed that Rev.io is a Great Place to Work compared to 57% agreement at comparable US-based companies, Rev.io stands out as a place where team, values and culture combine to create an amazing work environment!

About The Role: This hybrid role combines deep expertise in software engineering with AI/ML innovation. You&rsquo;ll join development efforts across both traditional and AI-powered systems, and serve as a technical bridge between LLMs, cloud solutions, and scalable software architecture. 
 
The Software Engineer &ndash; AI Solutions role will report directly to the Engineering Manager, and will work closely with the Engineering team, and other technology leaders to ensure that existing and new data solutions follow best practices and are highly performant. 
 
Key Responsibilities: 
AI &amp; Machine Learning
<ul><li>
Design, build, and optimize AI-powered applications using Azure OpenAI, LangChain, and Semantic Kernel</li><li>
Implement, fine-tune, and prompt-engineer large language models (LLMs) for Rev.io&rsquo;s business use cases</li><li>
Architect and manage vector databases, indexes, and retrieval pipelines</li><li>
Ensure AI systems are secure, scalable, and aligned with enterprise software best practices</li><li>
Stay ahead of AI trends, recommending tools and techniques that align with Rev.io&rsquo;s innovation goals</li></ul>

Software Engineering
<ul><li>Contribute to full-stack software development using .NET, SQL, React/Typescript, and Python</li><li>
Participate in sprint planning, backlog refinement, and architectural alignment for cross-functional teams</li><li>
Perform hands-on coding for high-impact, complex system components</li><li>
Engage and mentor in code reviews and architecture sessions with team members</li><li>
Work closely with Product and Design to deliver scalable, performant features</li><li>
Assist in troubleshooting and resolving production issues with AI or application layers</li><li>
Champion Agile principles, DevOps, and continuous improvement initiatives</li></ul>

Requirements:
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, or related field (or equivalent experience)</li><li>
5+ years in software engineering (preferably with leadership experience)</li><li>
3+ years hands-on with LLMs, Azure OpenAI, LangChain, vector databases</li><li>
Strong coding skills in both AI contexts (Python, prompt engineering) and enterprise development (.NET, React/TypeScript, SQL)</li><li>
Excellent communication and cross-functional collaboration skills</li><li>
Ability to translate AI concepts to business leaders and technical peers</li><li>
Familiarity with CI/CD, Azure DevOps, cloud-native architecture a strong plus</li></ul>
Employment eligibility is limited to individuals who currently reside in one of the following states: Florida, Georgia, Iowa, Kentucky, Maryland, Michigan, Missouri, North Carolina, Nebraska, New York, Ohio, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Virginia, Washington, Wisconsin, or West Virginia.

Benefits and Perks:
<ul><li>
Generous HSA employer contribution</li><li>
401k with generous company match and immediate vesting</li><li>
Unlimited PTO</li><li>
Paid Parental Leave</li><li>
Company paid for life and disability insurance</li><li>
Monthly tech reimbursement</li><li>
Monthly fitness reimbursement</li><li>
Education and development stipend</li><li>
Time off to volunteer at the organization of your choice, as well as company-level volunteer opportunities</li><li>
Clear and documented career path for your position</li><li>
True open-door policy with opportunities to give feedback to leadership on a continual basis through 1:1 sessions multiple times per year</li></ul>

At Rev.io no employee or applicant will be treated less favorably on the grounds of their sex, marital status, race, color, nationality or ethnic or national origin, disability, gender, sexual orientation, gender identity, age, pregnancy or maternity, marital or civil partner status, or religion or belief. By clicking submit below, you consent to allow Rev.io to store and process the personal information submitted above. 
 
#LI-hybrid</div>

Software Engineer - AI Solutions

The Home Depot

<div>Position Purpose:
The Staff Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Staff ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. 
Staff ML Engineers will be a core player on the product team and are expected to build and grow skillsets of more junior engineers. You will also be able to drive multiple ML initiatives by directing algorithm and technology product design 
Key Responsibilities:<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> 
Direct Manager/Direct Reports:<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> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<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> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
3 - 6 years of relevant work experience</li><li>
Experience to 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.</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</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 modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</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 NoSQL databases</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> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<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>

Staff Machine Learning Engineer (Remote)

<div>Position Purpose:
The Sr Machine Learning Engineer is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Sr ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
ML Engineers may be involved in designing and implementing AI/ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering. 
Sr ML Engineers should be able to operate independently though will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices. 
Key Responsibilities:<ul><li>
70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do &quot;destructive testing&quot; to ensure adequate resiliency in production; 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>
10% 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</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> 
Direct Manager/Direct Reports:<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> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<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> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
2 - 4 years of relevant work experience</li><li>
Experience to algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Experience to basic statistics and regression algorithms</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in modern web application framework such as Node.js</li><li>
Experience in a front-end technology and framework such as HTML, CCS, JavaScript, ReactJS, D3</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>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Familiarity with NoSQL databases</li><li>
Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Familiarity with defensive coding practices and patterns for high Availability</li><li>
Familiarity with A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
2</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<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>

Senior Machine Learning Engineer (Remote)

<div>Be part of something groundbreaking
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.
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.
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.
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.
Who we are
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.
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.
How you will create impact:
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.
Your responsibilities include:<ul><li>
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</li><li>
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</li><li>
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</li><li>
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</li><li>
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</li></ul>
What is needed to be successful:<ul><li>
Ph.D. with 2+ years&rsquo; industry experience</li><li>
Design and deploy Agentic AI solutions to automate complex business workflows, enhance decision-making, and improve customer and employee experiences.</li><li>
Translate research in agentic AI, reinforcement learning, and reasoning into practical solutions that support underwriting, Operation, claims automation, customer servicing, and risk assessment</li><li>
Experience implementing Agentic AI frameworks, such as CrewAI, Claude Agent sdk and LangChain, to build autonomous systems in production settings</li><li>
Strong ML, Deep Learning and Gen AI hand-on and scientific research skills</li><li>
Have produced novel research related to agentic design and implementation</li><li>
Experience in designing and implementing Model Context Protocol (MCP) servers to enable seamless integration between AI agents, enterprise systems, and external tools</li><li>
Specialized expertise in other topics like fine-tuning, RLHF, RAG and Knowledge graph etc.</li><li>
Experience in designing and implementing Model Context Protocol (MCP) servers to enable seamless integration between AI agents, enterprise systems, and external tools</li><li>
Knowledge of Palantir platforms will be plus</li><li>
Ph.D. Publication with GenAI and/or Agentic is a plus</li><li>
Are passionate about getting your work into the hands of real users and - more broadly - democratizing access to modern AI technology.</li><li>
Are motivated by working on Gen AI research that - contrary to the general trend in the field - will be disclosed to the public.</li><li>
Strong communication skills and a desire to work on a small, fast-paced team</li></ul>
Veterans are encouraged to apply. 
#LI-RG2 #LI-AIG #AI #GenAI #artificialintelligence #DataScience #BigData
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.
Enjoy benefits that take care of what matters
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.
Reimagining insurance to make a bigger difference to the world
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.
Welcome to a culture of inclusion
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.
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.
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.
<div><div><div><div><div><div><div>Functional Area:</div></div></div></div></div></div></div>
DT - Data
AIG PC Global Services, Inc.</div>

Ph.D. Research Data Scientist, GenAI

CapTech Consulting

<div>Company Description 
CapTech is an award-winning consulting firm that collaborates with clients to achieve what&rsquo;s possible through the power of technology. At CapTech, we&rsquo;re passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country. 
Job Description 
CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
Specific responsibilities for the Lead Machine Learning Engineer position include:
<ul><li>Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs</li><li>
Provide technical leadership and collaborate within and across teams to ensure that the overall technical solution is aligned with the customer needs.</li><li>
Deconstructing client needs into data-driven processes/models and analytical measures.</li><li>
Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).</li><li>
Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).</li><li>
Productionizing ML systems with a focus on optimization and scalability to satisfy clients&rsquo; requirements.</li><li>
Growing CapTech&rsquo;s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.</li></ul> 

Qualifications 
<ul><li>
7+ years of experience delivering data engineering and machine learning solutions on cloud platforms</li><li>
Bachelor's degree or equivalent combination of education and experience.</li><li>
Experience providing technical leadership and mentoring other engineers in data engineering space</li><li>
Hands-on experience manipulating and analyzing large (multi-billion record) data sets.</li><li>
Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.</li><li>
Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.</li><li>
Proficiency with containerization (e.g., Docker) and microservices.</li><li>
Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS</li><li>
Comfort and proficiency in framing data-driven problems from cross-industry business requirements.</li><li>
Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)</li><li>
Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).</li><li>
Knowledge of DevOps and automation best practices.</li><li>
Knowledge of statistics and statistical modeling methods.</li><li>
Knowledge of model management and model versioning best practices.</li><li>
Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting</li><li>
Experience with prompt engineering, MCP and RAG, and agentic AI architectures</li><li>
Strong understanding of conversational UX and prompt evaluation metrics</li><li>
Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)</li><li>
Experience with multi-agent orchestration</li></ul> 

Additional Information 
We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we&rsquo;ve launched extended benefits to help meet our employees&rsquo; needs.<ul><li>
Learning &amp; Development &ndash; Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths</li><li>
Modern Health &ndash;A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life&rsquo;s ups and downs</li><li>
Carrot Fertility &ndash;Inclusive fertility and family-forming coverage for all paths to parenthood &ndash; including adoption, surrogacy, fertility treatments, pregnancy, and more &ndash; and opportunities for employer-sponsored funds to help pay for care</li><li>
Fringe &ndash;A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them &ndash; ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more</li><li>
Employee Resource Groups &ndash; Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations</li><li>
Philanthropic Partnerships &ndash; Opportunities to engage in partnerships and pro-bono projects that support our communities.</li><li>
401(k) Matching &ndash; Generous matching and no vesting period to help you continue to build financial wellness</li></ul>
CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness &mdash; each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com. At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.</div>

Lead Machine Learning / Data Science Engineer

Cox Automotive

<div>What You'll Do: 
 
The Senior Cyber Security Engineer is a highly skilled, hands-on technical contributor responsible for engineering, deploying, administering, and continuously improving enterprise security technologies that protect both Corporate Computing (team member endpoints) and Enterprise Computing environments (on-prem, cloud, and hybrid). 
 
In this role, you will apply deep security engineering expertise, modern automation practices, and strong platform ownership to help ensure our security controls are resilient, scalable, and effective against evolving threats. You will collaborate closely with engineering, architecture, SOC, cloud, IAM, and product teams to embed security into platforms, services, and workflows. 
 
This role is ideal for an experienced security engineer who thrives at the intersection of Security Engineering, DevSecOps, cloud security, platform automation, and emerging AI-driven capabilities, and who enjoys solving complex technical problems at scale. 
 
Key Responsibilities: 
 
Security Tooling Engineering, Deployment &amp; Administration 
<ul><li>
Engineer, deploy, configure, tune, and maintain core security platforms including EDR, SASE, ZTNA, Email Security, Network Firewalls, DDoS, SIEM, SOAR, Firewall Audit, KMS, and related endpoint, network, data protection, and cloud security technologies.</li><li>
Support lifecycle activities such as upgrades, feature adoption, performance tuning, and operational improvements across security platforms.</li><li>
Evaluate and test new vendor capabilities and enhancements, partnering with senior engineers and architects to operationalize improvements.</li><li>
Contribute to scalable, resilient architectures for endpoint and enterprise security systems across on-prem, cloud, and SaaS environments.</li></ul> 

Automation &amp; Infrastructure-as-Code (IaC) 
<ul><li>
Automate security infrastructure provisioning, configuration, and policy deployment using Terraform, Git-based workflows, CI/CD pipelines, and DevSecOps practices.</li><li>
Develop and maintain reusable modules, pipelines, and templates that standardize how security controls are deployed and integrated.</li><li>
Contribute to Security-as-Code and Policy-as-Code initiatives that embed security guardrails into engineering workflows.</li></ul> 

Security Architecture &amp; Engineering Collaboration 
<ul><li>
Partner with engineering, cloud, and platform teams to provide hands-on security engineering guidance and design input.</li><li>
Contribute to secure-by-default patterns, architecture standards, reference implementations, and best practices.</li><li>
Identify security control gaps and work collaboratively to design pragmatic, scalable solutions.</li></ul> 

AI-Driven Security Engineering &amp; Automation 
<ul><li>
Apply AI and automation techniques to reduce manual effort, improve operational efficiency, and enhance security tooling integrations.</li><li>
Contribute to internal automation initiatives that support SOC workflows, threat investigation, identity security, and data protection.</li><li>
Assist with the evaluation and operational use of AI/ML features within security tools (e.g., risk scoring, behavioral analytics, anomaly detection).</li></ul> 

Security Control Enhancement &amp; Continuous Improvement 
<ul><li>
Participate in proofs of concept (POCs), feature evaluations, and capability assessments across the security stack.</li><li>
Help develop dashboards, metrics, and telemetry that measure security control health, effectiveness, and drift.</li><li>
Collaborate with SOC and threat intelligence teams to align engineering improvements with real-world threat activity.</li></ul> 

Cross-Platform Security Coverage 
<ul><li>
Engineer and support security controls across:</li><li>
Corporate Computing: team member endpoints (Windows, macOS, Linux), secure remote access, identity and access workflows</li><li>
Enterprise Computing: datacenter infrastructure, cloud platforms (AWS, Azure, GCP), containers/Kubernetes, and hybrid workloads</li></ul> 

Who You Are: 
 
Minimum Requirements: 
<ul><li>
Bachelor's degree in a related discipline and 4 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 2 years' experience; a Ph.D. and up to 1 year of experience; or 16 years' experience in a related field</li><li>
4 years of experience in Cyber Security Engineering, Security Architecture, Platform Engineering, or related disciplines.</li><li>
Strong hands-on experience administering and engineering major security platforms (e.g., EDR, SASE, ZTNA, Email Security, Network Firewalls, SIEM/SOAR, KMS).</li><li>
Demonstrated experience automating infrastructure and security tooling using Terraform, CI/CD pipelines, GitOps, and scripting languages (Python preferred).</li><li>
Solid understanding of cloud platforms, identity security, endpoint security, and zero-trust architectures.</li><li>
Experience contributing to secure enterprise architectures at scale.</li><li>
Strong communication skills and the ability to collaborate effectively with cross-functional engineering teams.</li></ul> 

Preferred 
<ul><li>
Experience applying AI or automation to security operations, detection engineering, or cloud security workflows.</li><li>
Hands-on experience with EDR tuning, DLP policy engineering, cloud workload protection, and modern SIEM/SOAR pipelines.</li><li>
Security or cloud certifications such as CISSP, CCSP, GCSA, GCPN, GCIA, or vendor-specific credentials.</li></ul> 

Why Join Us 
<ul><li>
Work on high-impact security engineering initiatives across large-scale, complex hybrid environments.</li><li>
Operate and improve a world-class security tool stack with growing investment in automation and AI.</li><li>
Collaborate with senior + lead engineers, architects, and security leadership to modernize security controls.</li><li>
Build deep technical expertise while directly improving the security posture of thousands of endpoints, cloud assets, and enterprise systems.</li></ul> 
USD 121,800.00 - 203,000.00 per year 
 
Compensation: 
 
Compensation includes a base salary of $121,800.00 - $203,000.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program. 
 
Benefits: 
 
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.</div>

Cybersecurity Senior Engineer

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