We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting-edge research with the responsibility of building a culture of continuous learning and knowledge sharing. You'll lead efforts to identify, evaluate, and prototype emerging ML technologies while establishing our company as a thought leader in the ML community. Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and improve data quality. Structures, trains, and deploys models to learn from complex data across multiple modalities (e.g., structured, unstructured, image, video, audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least one sub-area of machine learning, such as deep learning, generative AI, computer vision, optimization, predictive models, or causal machine learning.
WHAT YOU'LL DO
Key Responsibilities
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Accelerate ML development using AI tools for code generation, feature engineering, optimization, and validation
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Stay up to date with advancements in ML, AI, and emerging technologies
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Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference
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Optimize model performance, scalability, and reliability in production environments
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Collaborate cross-functionally to translate model insights into business value and communicate project updates
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Contribute to ML infrastructure improvements, best practices, and documentation
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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.
- Analyzes complex data sets to solve real-world business and customer use cases.
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Performs end-to-end development of machine learning models
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May assist with or lead the development of industry whitepapers or other technical publications.
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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.
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Key AI Use Cases
- AI-Accelerated Model Development: Use GitHub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
- Agentic ML Workflows: Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training pipelines, multi-step analysis, and collaborative research.
- AI-Enhanced Model Interpretation: Build on traditional frameworks (SHAP, LIME) with AI tools for enhanced stakeholder communication and automated insights.
- AI-Powered Research: Leverage manual/autonomous competitive intelligence and research acceleration tools for methodology discovery and algorithm innovation.
WHO YOU ARE
Required Skills
- Proficiency in AI development tools (GitHub Copilot, Claude, GPT-4) for ML development with ability to validate AI outputs for production readiness.
- Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain, agent patterns) with progression 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 leverage 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.
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Required Qualifications
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Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
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Bachelor's degree in a related discipline and 6 years' experience in Machine Learning; or a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 years' experience in a related field; or 18 years' experience in a related field with no degree
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Minimum of 6 years of experience as a Machine Learning Engineer or equivalent
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Deep expertise in multiple ML domains and familiarity with emerging research areas
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Strong experience in technology evaluation, competitive analysis, and strategic planning
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Comfortability with non-deterministic systems
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Product background- understand how to prioritize, collaborate across teams, manage dependencies with others, set strategy
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Experience in Rally, Jira or similar tools
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Skilled in analytical thinking, consulting, requirements analysis, system and technology integration and technology savvy.
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Skilled in collaborating with intent, communicating with impact, developing trust, driving innovation and striving for excellence.
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Proven track record of leading innovative projects from concept to proof-of-concept
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Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.)
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Experience building and leading high-performing research or innovation teams
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Excellent communication skills for technical and executive audiences
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Strong network within the ML research community
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Experience with research collaboration and partnership development
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Other duties as needed or required
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Must be comfortable with change and an evolving environment
Preferred Qualifications
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Experience in corporate research labs, innovation teams, or technology consulting
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Track record of identifying and successfully implementing breakthrough technologies
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Background in technology transfer from research to business applications
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Strong presence in the ML community (conference speaking, open-source contributions, etc.)
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Knowledge of emerging areas such as LLMs, Agents, foundation models, multimodal AI, or quantum ML
Leadership Expectations
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Foster a culture of experimentation, learning, and calculated risk-taking
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Drive consensus on research priorities while maintaining innovation velocity
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Develop talent through mentoring in both technical skills and research methodologies
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Communicate complex experimental results and strategic implications to all organizational levels
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Lead by example in intellectual curiosity, scientific rigor, and knowledge sharing
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Build bridges between cutting-edge research and practical business applications
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Establish the team as a recognized center of excellence in experimental ML
USD 134,900.00 - 224,900.00 per year
Compensation:
Compensation includes a base salary in the range of $134,900.00 - $224,900.00. 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.
EOE, including disability/vets
