AI/ML Engineer - 25-02707

Job Description LeadStack Inc. is an award winning, one of the nation's fastest growing, certified minority owned (MBE) staffing services provider of contingent workforce. As a recognized industry leader in contingent workforce solutions and Certified as a Great Place to Work, we're proud to partner with some of the most admired Fortune 500 brands in the world. Job Title: AI/ML Engineer Duration:12 months Location: Stanford, CA 94305 (Hybrid) Position Overview The AI/ML Engineer will be a key technical contributor driving CGOE’s AI transformation initiatives, with a focus on building and deploying intelligent, cloud-native applications including GenAI-powered systems, retrieval-augmented assistants, and data-driven automation workflows. Working at the intersection of machine learning, cloud engineering, and educational innovation, this role converts complex requirements into scalable, secure, and maintainable AWS-native AI systems that enhance teaching, learning, and operations across CGOE’s global online programs. Top Requirements • 3+ years deploying AI/ML applications in production environments. • Strong experience with Python and AWS (serverless, microservices, CI/CD, IAM). • At least one AWS Associate-level certification (e.g., Solutions Architect Associate, Developer Associate, SysOps Administrator Associate, Data Engineer Associate). Key Responsibilities AI Application & Systems Development • Own the design and end-to-end implementation of AI systems combining GenAI, narrow AI, and traditional ML models (e.g., regression, classification). • Implement retrieval-augmented generation (RAG), multi-agent, and protocol-based AI systems (e.g., Model Context Protocol/MCP) using modern frameworks such as LangChain and LlamaIndex or similar. • Integrate AI capabilities into production-grade applications using serverless and containerized architectures (AWS Lambda, Fargate, ECS). • Fine-tune and optimize existing models for specific educational and administrative use cases, focusing on performance, latency, and reliability. • Build and maintain data pipelines for model training, evaluation, and monitoring using AWS services such as Glue, S3, Step Functions, and Kinesis. Cloud & Infrastructure Engineering • Architect and manage scalable AI workloads on AWS leveraging services such as SageMaker, Bedrock, API Gateway, EventBridge, and IAM-based security. • Build microservices and APIs to integrate AI models into applications and backend systems. • Develop automated CI/CD pipelines to ensure continuous delivery, observability, and monitoring of deployed workloads (e.g., GitHub Actions, CodePipeline). • Apply containerization best practices using Docker and manage workloads via AWS Fargate and ECS for scalable, serverless orchestration and reproducibility. • Ensure compliance with • • (e.g., FERPA, GDPR-style requirements) for secure data handling and governance. Collaboration, Culture & Continuous Improvement • Collaborate with cross-functional teams (engineering, product, academic stakeholders, operations) to deliver integrated and impactful AI solutions. • Use Git-based version control and follow code review best practices as part of a collaborative, agile workflow. • Operate within an agile, iterative development culture, participating in sprints, retrospectives, and planning sessions. • Continuously learn and adapt to emerging AI frameworks, AWS tools, and cloud technologies, contributing to documentation, internal knowledge sharing, and mentoring as the team scales. Requirements Education & Certifications • Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred). • At least one AWS Associate-level certification required; professional-level or specialty certifications (e.g., Machine Learning Specialty, Advanced Networking, Security) are a plus. Experience • 3+ years of experience developing and deploying AI/ML-driven applications in production environments. • 2+ years of hands-on experience with AWS-based architectures (serverless, microservices, CI/CD, IAM). • Proven ability to design, automate, and maintain data pipelines for model inference, evaluation, and monitoring. • Experience with both GenAI and traditional ML techniques in applied, production settings. Technical Skills • Languages: Python (required); familiarity with Go, Rust, R, or TypeScript preferred. • AI/ML Frameworks: PyTorch, TensorFlow, LangChain, LlamaIndex, or similar libraries for RAG and agentic workflows. • Cloud & Infrastructure: AWS SageMaker, Bedrock, Lambda, ECS/Fargate, API Gateway, EventBridge, Glue, S3, Step Functions, IAM, CloudWatch. • Infrastructure as Code: AWS CloudFormation. • DevOps & Tools: Git, Docker, AWS Fargate, ECS, CI/CD (GitHub Actions, CodePipeline). • Data Systems: SQL/NoSQL databases, vector databases, and AWS-native data services for AI workloads. Desired Attributes • Strong understanding of data engineering fundamentals and production-quality AI system design. • Passion for applying AI to improve educational outcomes and operational efficiency. • Excellent problem-solving, debugging, and communication skills. • Demonstrated ability to learn rapidly, adapt to new technologies, and continuously improve. • Commitment to ethical AI, data privacy, and transparency. • Collaborative mindset with proven success in agile, team-based environments. • Thrives in a fast-paced, evolving environment and proactively seeks opportunities to upskill and enhance processes. Success Metrics • Timely delivery of scalable, maintainable AI solutions that meet stakeholder needs. • High system uptime, performance, and cost-efficiency of deployed workloads. • Consistent adoption of best practices in CI/CD, monitoring, and version control. • Positive stakeholder feedback and meaningful contributions to team documentation, learning, and innovation initiatives. know more about current opportunities at LeadStack , please visit us on https://leadstackinc.com/careers/ Should you have any questions, feel free to call me on (513) 3184502 or send an email on waseem.ahmad@leadstackinc.com