Machine Learning Lead Engineer

Compensation

Base salary range: $ – $. Eligible for additional incentive program.

We are seeking a visionary Machine Learning Lead Engineer to spearhead experimental ML initiatives and drive innovation across the organization.

• Accelerate ML development using AI tools for code generation, feature engineering, optimization, and validation.
• Stay up to date with advancements in ML, AI, and emerging technologies.
• Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference.
• Optimize model performance, scalability, and reliability in production environments.
• Collaborate cross‑functionally to translate model insights into business value and communicate project updates.
• Contribute to ML infrastructure improvements, best practices, and documentation.
• Partner with engineering teams to integrate AI‑enhanced models and establish automated monitoring frameworks.
• Establish AI governance practices including bias detection, interpretability, compliance monitoring, and responsible deployment.
• Mentor teams in AI adoption, share best practices, and promote responsible AI innovation culture.
• Lead AI transformation initiatives including tool evaluation, governance development, and strategic adoption planning.
• Analyze complex data sets to solve real‑world business and customer use cases.
• Perform end‑to‑end development of machine learning models.
• Assist with or lead the development of industry whitepapers or other technical publications.
• Continuously evaluate AI processes for accuracy, efficiency, and business impact while staying current on emerging technologies.
• Design agentic workflows for autonomous training, data pipelines, and analytical problem solving appropriate to experience level.

• AI‑Accelerated Model Development:
  Use tools such as Git Hub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
• Agentic ML Workflows:
  Deploy AWS Agent Squad, AWS Strands, Lang Chain agents for autonomous training pipelines, multi‑step analysis, and collaborative research.
• AI‑Enhanced Model Interpretation:
  Build on frameworks (SHAP, LIME) with AI tools for enhanced stakeholder communication and automated insights.
• AI‑Powered Research:
  Leverage competitive intelligence and research acceleration tools for methodology discovery and algorithm innovation.

• Proficiency in AI development tools (Git Hub Copilot, Claude, GPT‑4) for ML development and validation of AI outputs for production readiness.
• Understanding of agentic frameworks (AWS Agent Squad, AWS Strands, Lang Chain) from basic configuration to custom enterprise system design.
• Knowledge of AI ethics, responsible AI practices, and governance frameworks for business‑critical ML deployment.
• Ability to use AI like Co‑Pilot for technical communication to stakeholders and cross‑functional collaboration.
• Commitment to continuous learning in AI‑augmented data science and responsible AI use.

• Current authorization to work in the United States without sponsorship.
• Bachelor’s degree in a related discipline and 6 years’ experience in Machine Learning (or equivalent combinations of education and experience).
• Deep expertise in multiple ML domains and familiarity with emerging research areas.
• Strong experience in technology evaluation, competitive analysis, and strategic planning.
• Comfortable with non‑deterministic systems.
• Product background that includes prioritizing, collaborating across teams, managing dependencies, and setting strategy.
• Experience with Rally, Jira or similar tools.
• Skilled in analytical thinking, consulting, requirements analysis, system and technology integration, and…