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ml 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

The Home Depot

<div>Position Purpose:
The Machine Learning Engineer II 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. 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. 
ML Engineers should be able to operate independently with minimum guidance from others, although 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>
65% 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; Program configuration/modification and setup activities on large projects using HD approved methodology; 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</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>
1 - 3 years of relevant work experience</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc</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>
Familiarity with algorithms such as clustering, forecasting, anomaly detection, and neural networks.</li><li>
Familiarity with basic statistics and regression algorithms</li><li>
Familiarity with advanced statistics such as bayesian statistics</li><li>
Familiarity with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.</li><li>
Familiarity with Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and AutoML</li><li>
Familiarity with a Linux or Unix based environment</li><li>
Familiarity with a CI/CD toolchain</li><li>
Familiarity with REST and effective web service design</li><li>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</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>
1</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>

Machine Learning Engineer II (Remote)

<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)

DS Technologies Inc

<div><div><div>About US: We are a company that provides innovative, transformative IT services and solutions. We are passionate about helping our clients achieve their goals and exceed their expectations. We strive to provide the best possible experience for our clients and employees. We are committed to continuous improvement and innovation, and we are always looking for ways to improve our services and solutions. We believe in working collaboratively with our clients and employees to achieve success.</div>
<div></div>
<div>DS Technologies Inc is looking for AI Architect role for one of our premier clients. 
</div><div>Job Title: AI Architect 
Location: Hartford, CT and Atlanta, GA 
Position Type: Contract 
Only W2 
 
Position Overview: 
 
We are seeking an AI Architect to lead the design, development, and deployment of AI-powered capabilities for our next-generation insurance product. This role will be responsible for defining the AI architecture, integrating advanced machine learning models, collaborating with actuarial and underwriting teams, and ensuring scalable, secure, and compliant AI solutions across the product lifecycle. 
 
Key Responsibilities: 
AI Architecture &amp; Solution Design 
</div><ul><li>Design end-to-end AI/ML architecture for insurance-specific use cases such as underwriting automation, risk scoring, fraud detection, customer personalization, and pricing optimization.</li>
<li>Select and define the appropriate AI technologies, model architectures (LLMs, predictive ML, NLP, vision models), and data pipelines.</li>
<li>Build scalable ML systems using cloud-native solutions (AWS, Azure, or GCP) and ML Ops frameworks.</li>
</ul><div>Insurance Product Development</div>
<ul><li>Collaborate with product managers, actuaries, and underwriting SMEs to translate insurance product requirements into AI-enabled functional components.</li>
<li>Develop AI models that support rating algorithms, claims triage, eligibility checks, policy servicing workflows, and agent enablement.</li>
<li>Ensure AI outputs comply with insurance regulations, underwriting guidelines, and internal governance.</li>
</ul><div>Model Engineering &amp; Deployment</div>
<ul><li>Lead development, training, validation, and deployment of ML models.</li>
<li>Implement MLOps pipelines for automated model testing, monitoring, drift detection, and versioning.</li>
<li>Optimize AI performance for accuracy, fairness, explainability, and scalability.</li>
</ul><div>Security, Compliance &amp; Risk Management</div>
<ul><li>Ensure data privacy and security compliance (e.g., HIPAA, GDPR, ISO standards depending on geography).</li>
<li>Implement responsible AI frameworks including explainability, bias mitigation, and model auditability.</li>
<li>Collaborate with risk and compliance teams to meet regulatory expectations for insurance AI models.</li>
</ul><div>Cross-Functional Collaboration</div>
<ul><li>Partner with engineering, actuarial science, underwriting, and IT operations teams.</li>
<li>Provide technical leadership and mentoring to data scientists, ML engineers, and developers.</li>
<li>Drive innovation through POCs, technology evaluations, and continuous modernization.</li>
</ul><div>Required Qualifications: 
Technical Skills:
</div><ul><li>4+ years of experience in AI/ML engineering, architecture</li>
<li>Expertise in ML frameworks, LLMs, NLP, and generative AI.</li>
<li>Strong background in cloud architecture (Azure).</li>
<li>Experience implementing MLOps (CI/CD pipelines, model monitoring tools).</li>
<li>Hands-on experience with APIs, microservices, and containerization (Docker, Kubernetes).</li>
</ul><div>Insurance Industry Experience:</div>
<ul><li>Deep understanding of insurance processes in at least one line of business:</li>
<li>P&amp;C (auto, home, commercial)</li>
<li>Experience building or integrating models for underwriting, rating, or fraud detection.</li>
<li>Soft Skills</li>
<li>Strong analytical and problem-solving abilities.</li>
<li>Excellent communication skills with the ability to explain AI concepts to non-technical stakeholders.</li>
<li>Ability to lead cross-functional teams in a fast-paced environment.</li>
</ul><div>Preferred Qualifications</div>
<ul><li>Bachelor&rsquo;s or master&rsquo;s in computer science, AI, or related field.</li>
<li>Certifications in cloud architecture ( Azure Architect).</li>
<li>Experience with interpretable ML techniques relevant to regulated industries.</li>
<li>Background in actuarial science or insurance analytics is a strong plus.</li></ul></div></div>

AI Architect

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</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. 
 
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. 
 
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.
 
 
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. 
 
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. 
 
Travel up to 50% may be possible. 
 
Key job responsibilities 
- 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. 
<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> 
About the team 
Diverse Experiences 
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.
 
Why AWS? 
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. 
Inclusive Team Culture 
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. 
Mentorship &amp; Career Growth 
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.
 
Work/Life Balance 
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"> 
BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</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> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
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. 
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. 
USA, CA, Mountain View - 176,600.00 - 239,000.00 USD annually 
USA, CA, San Francisco - 176,600.00 - 239,000.00 USD annually 
USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually 
USA, NJ, Jersey City - 169,000.00 - 228,600.00 USD annually 
USA, NY, New York - 169,000.00 - 228,600.00 USD annually 
USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually 
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually</div>

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

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

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