Lead I - ML Engineering
- AI
- Machine Learning
- Natural Language Processing
- RAG
- MLOps
- AI/ML
- PyTorch
- TensorFlow
- scikit-learn
- GPT
- Databricks
- Azure
- AWS
- GCP
We are seeking a highly accomplishedAI Lead with 6+ years of industry experience to shape, lead, and delivernext-generation AI solutions across complex, real world problems. This role is ideal for a hands-on technical leader with deep expertise inclassical Machine Learning,Generative AI, andAgentic AI systems, and a passion for buildingintelligent automation solutions at scale.
The ideal candidate will have a strong track record of leadingend-to-end AI programs, delivering impactful solutions acrossmultiple industries, and translating cutting-edge research into production-grade systems. Experience withLLMs, autonomous agents, and AI-driven workflows will be critical to success in this role.
Key Responsibilities
- AI Program Leadership: Lead the design, execution, and delivery of complex AI initiatives from problem framing and architecture to production rollout ensuring clear business impact and measurable outcomes.
- Technical Thought Leadership: Act as a hands-on technical authority inML, Deep Learning, NLP, Generative AI, and Agentic AI, guiding solution design for intelligent automation, decision intelligence, and autonomous systems.
- Intelligent Automation & AI Systems: Architect and drive AI-powered automation solutions using predictive models, LLMs, and agent-based workflows to solve challenging, high-value enterprise problems.
- Innovation & R&D: Continuously evaluate emerging AI trends, tools, and research (e.g., multi-agent systems, RAG, LLM fine-tuning, Reasoning models) and apply them pragmatically to real-world use cases.
- Team Leadership & Mentorship: Build, mentor, and inspire high-performing AI teams, providing technical direction, code/design reviews, and career guidance for data scientists and ML engineers.
- Cross-Functional Collaboration: Work closely with product, engineering, and business stakeholders to identify AI opportunities, define solution roadmaps, and ensure seamless integration into enterprise systems.
- Quality, Reliability & MLOps: Ensure AI solutions meet high standards of accuracy, robustness, scalability, and observability through strong MLOps practices and continuous monitoring.
- Strategic Contribution: Contribute to enterprise AI strategy, capability building, and long-term roadmaps aligned with organizational growth and innovation goals.
Qualifications & Experience
- Bachelor s degree inComputer Science, Engineering, Mathematics, or a related field;Master s or PhD preferred.
- 6+ years of hands-on experience delivering AI/ML solutions, with strong depth inclassical ML, deep learning, and NLP.
- Proven experience leading and deliveringmultiple large-scale AI projects from idea to production across diverse domains.
- Strong expertise inML frameworks such asPyTorch, TensorFlow, Scikit-learn, and modern deep learning architectures.
- Demonstrated experience withGenerative AI and LLMs (e.g., GPT, BERT, Transformers), including RAG, fine-tuning, and agent-based systems.
- Solid experience withMLOps,Databricks, and cloud-native AI platforms (Azure, AWS, GCP).
- Strong understanding of designing AI systems forintelligent automation, decision support, and autonomous workflows.
- Excellent leadership, communication, and stakeholder-management skills.
- Strong analytical mindset with a proven ability to solve ambiguous, high-impact problems in fast-paced environments.
Lead I - ML Engineering · UST