Machine Learning Lead Engineer

CAI Cox Automotive Corp Svcs., LLC; Atlanta (GA); On-site; USD 134,900 - 224,900; Full time

Benefits offered by this job

Flexible vacation policy

Health insurance (medical, dental, vision)

401(k) retirement planning

Paid wellness time

Job summary

CAI Cox Automotive Corp Svcs., LLC is looking for a visionary Machine Learning Lead Engineer in Atlanta, Georgia, to spearhead innovative ML initiatives. The role involves managing ML development, designing robust pipelines, and optimizing model performance while collaborating cross-functionally to drive organizational innovation.

The ideal candidate will have a Bachelor’s degree and 6 years of experience in Machine Learning, alongside strong proficiency in AI development tools. The position also offers a flexible vacation policy along with comprehensive health benefits.

Qualifications

• Current authorization to work in the U.S. without sponsorship.
• 6 years’ experience in Machine Learning or equivalent.
• Expertise in multiple ML domains and familiarity with emerging research.

Responsibilities

• Lead experimental ML initiatives and drive innovation.
• Accelerate ML development using AI tools.
• Design and maintain ML models and pipelines.

Skills

AI development tools (GitHub Copilot, Claude, GPT‑4)

Agentic frameworks (AWS AgentSquad, AWS Strands, LangChain)

AI ethics and governance frameworks

Technical communication skills

Commitment to continuous learning

Education

Bachelor’s degree in a related discipline

Tools

Rally

Jira

Job description

Compensation

Base salary range: $134,900.00 – $224,900.00. Eligible for additional incentive program.

Job Description

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

Key Responsibilities

• 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.

Key AI Use Cases

• AI‑Accelerated Model Development: Use tools such as GitHub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
• Agentic ML Workflows: Deploy AWS AgentSquad, AWS Strands, LangChain 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.

Required Skills

• Proficiency in AI development tools (GitHub Copilot, Claude, GPT‑4) for ML development and validation of AI outputs for production readiness.
• Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain) 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.

Required Qualifications

• 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 technology savvy.
• Skilled in communicating with impact, developing trust, driving innovation, and striving for excellence.
• Proven track record of leading innovative projects from concept to proof‑of‑concept.
• Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.).
• Experience building and leading high‑performing research or innovation teams.
• Excellent communication skills for technical and executive audiences.
• Strong network within the ML research community.
• Experience with research collaboration and partnership development.
• Comfortable with change and an evolving environment.

Preferred Qualifications

• Experience in corporate research labs, innovation teams, or technology consulting.
• Track record of identifying and successfully implementing breakthrough technologies.
• Background in technology transfer from research to business applications.
• Strong presence in the ML community (conference speaking, open‑source contributions, etc.).
• Knowledge of emerging areas such as LLMs, Agents, foundation models, multimodal AI, or quantum ML.

Leadership Expectations

• Foster a culture of experimentation, learning, and calculated risk‑taking.
• Drive consensus on research priorities while maintaining innovation velocity.
• Develop talent through mentoring in technical skills and research methodologies.
• Communicate complex experimental results and strategic implications to all organizational levels.
• Lead by example in intellectual curiosity, scientific rigor, and knowledge sharing.
• Build bridges between cutting‑edge research and practical business applications.
• Establish the team as a recognized center of excellence in experimental ML.

Drug Testing

This role requires a pre‑employment drug test, except for marijuana testing which is not required. The workplace is drug‑free; possession, use, or influence of illegal drugs during work hours, on company property, or in company vehicles is prohibited.

Benefits

• Flexible vacation policy aligned with duties and company needs.
• Seven paid holidays per calendar year.
• Up to 160 hours of paid wellness annually.
• Additional paid time off: bereavement leave, voting leave, jury duty leave, volunteer time off, military leave, and parental leave.
• Health insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, or PTO).

Equal Employment Opportunity Statement

Cox Automotive is an Equal Employment Opportunity employer – All qualified applicants/employees will receive consideration for employment without regard to age, race, color, religion, creed, national origin, sex, sexual orientation, gender identity, disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Reasonable accommodations are provided when requested unless they cause undue hardship.