Director, Machine Learning Engineering

The AIML Director is a senior technology leader responsible for defining and driving the enterprise strategy across AI, Machine Learning, and Generative AI. This role owns the long term roadmap for AI/ML solutions, platforms, models, and engineering capabilities. The Director will lead a high-performing organization across data science, machine learning engineering, or GenAI/platform engineering (depending on assignment), ensuring scalable, secure, and innovative solutions that deliver measurable business impact.
The Director operates as a cross-functional thought leader, partnering with Product, Engineering, Analytics, Infrastructure, and executive stakeholders to advance the company’s AI maturity and accelerate responsible, value-oriented AI adoption.

Outcomes and Activities

• Strategic Leadership
  • Define and communicate the long-term vision for ML/AI applications and engineering, aligning with corporate strategy.
  • Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively.
• Execution & Delivery
  • Oversee design, development and deployment of enterprise-scale ML/AI solutions, inference pipelines, and respective technical roadmaps.
  • Ensure operational excellence in ML/LLM Ops, including automation, observability, and lifecycle management in partnership with the AIML platform engineering team
• Innovation
  • Champion adoption of cutting-edge techniques (Deep learning, recommendation engine architecture, graph neural networks, causal inference, LLMs, RLs, etc).
  • Drive responsible AI practices, model interpretability, and compliance with regulatory requirements.
• Team Development
  • Build and mentor a high-performing organization of managers and senior engineers.
  • Foster a culture of continuous learning, experimentation, and engineering craftsmanship.
• Governance & Risk
  • Establish standards for security, scalability, and architectural integrity across ML/AI systems.
  • Implement robust governance for data privacy, ethical AI, and risk mitigation.

Competencies: The following items detail how you will be successful in this role.

• Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer’s shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience.
• Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves pursuing and achieving high standards, best practices, innovation, and superior solutions.
• One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively.
• Owner’s Mindset: Owner’s Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business.

Requirements

• Education & Experience
  • PhD in Computer Science, Statistics and related field with 10+ years in Machine Learning engineering (preferred); or MS with 12+ years of experience.
  • Minimum 5 years in senior leadership roles managing managers and large engineering teams.
• Technical Expertise
  • Proven track record in building production-grade ML systems with strong problem-solving skills
  • Hands-on experience building different types of models (ex: large-scale real-time Recommendation models, Causal Inference, Offer optimization, RL, multi-layer DL algorithms, Propensity, Churn, etc.) and scientific solutions
  • Deep knowledge of ML lifecycle tools (MLflow, Kubeflow), distributed systems, and cloud-native architectures.
• Leadership Skills
  • Passion to solve problems and drive value-based transformative changes
  • Ability to influence C-suite stakeholders and communicate complex technical concepts clearly.
  • Experience in strategic planning, budgeting, and organizational scaling.
  • Experience building, training and developing engineering teams

Target Compensation: A competitive base salary range from $205,561 – $301,490.  This position is eligible for an annual variable bonus of cash and equity, between 10-20%. Bonus amounts are based on individual performance. Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications. 

Candidates who reside in the following major metropolitan areas may be eligible for a premium on top of the posted range based on their specific zone: San Francisco, Seattle, Boston, New York City, Los Angeles and San Diego. 

INDENGLP

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Benefits

• Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work 

Our Company Values:

To be successful in this role, Team Members need to be:

• Positive by maintaining resiliency and focusing on solutions
• Respectful by collaborating and actively listening
• Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions
• Direct by effectively communicating and conveying courage
• Earnest by taking accountability, applying feedback and effectively planning and priority setting

To create an environment where people do their best work, we focus on the dimensions of Organizational Health. All leaders must:

• Identify the Right People by recognizing top talent
• Set Clear Expectations by managing change and directing others
• Train team members and focus on developing talent
• Performance Manage by ensuring accountability and driving results
• Create the Right Environment by establishing trust and managing conflict
• Maintain the Right Number of team members needed to build an effective team

Expectations:

• Remain compliant with our policies processes and legal guidelines
• All other duties as assigned
• Attendance as required by department

Advice!

We understand that your career search may look different than others. Our hiring team wants to make sure that this would be a fit not just for us, but for you long term.  If you are actively looking or starting to explore new opportunities, send us your application!

 

P.S.

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