Staff/ Principal Machine Learning (AI) Engineer

Responsibilities:

Technical Leadership
• Define and drive the architectural vision for ML and LLM systems that power personalization, intelligent recommendations, and real-time decision-making.
• Lead the development of reliable, scalable ML infrastructure for training, inference, monitoring, and lifecycle management.
• Establish foundational design patterns and best practices for ML observability, testing, and performance.
• Mentor senior and lead engineers, fostering a culture of system ownership, clarity, and innovation.
Strategy & Architecture
• Build and maintain scalable, secure data and ML infrastructure to support advanced use cases.
• Architect robust pipelines for training, evaluation, deployment, and monitoring of ML and LLM models.
• Partner with internal delivery, engineering teams, and clients to translate complex problems into scalable ML solutions.
• Lead architecture design discussions with C-level client stakeholders, balancing scalability, cost, and performance.
Presales & Consulting
• Engage with clients and prospects in presales cycles to understand their needs, design tailored ML/AI and Data solutions, and demonstrate technical feasibility.
• Collaborate with sales and business development teams to create proposals, proofs of concept, and technical presentations.
• Act as a trusted advisor by consulting with clients on best practices for Data/ML adoption, infrastructure strategy.
• Represent the company at industry events, conferences, and client workshops as a thought leader in ML and AI.
Practice Growth & Enablement
• Grow and mature the ML practice by developing methodologies, frameworks, and reusable assets that accelerate solution delivery.
• Foster knowledge-sharing across squads, building a strong internal community of practice around ML/AI/ Data.

Qualifications:

• 7–10+ years of experience in Machine Learning Engineering, with 3+ years in technical leadership.
• Deep expertise in ML infrastructure, including training pipelines, model lifecycle management, and monitoring.
• Proven success in deploying production-grade ML systems at scale.
• Hands-on experience with AI, LLMs, and data engineering.
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).
• Experience with data engineering and cloud platforms (AWS, GCP, Azure, Snowflake, Spark, Airflow).
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Demonstrated success in presales or consulting engagements, including building client relationships and delivering technical proposals.
• Advanced degree (MSc/PhD) in Computer Science, Machine Learning, or related field preferred.
• Excellent communication and cross-organizational leadership skills.

What We Offer:

• Opportunity to work at the forefront of AI/ML and data technologies, driving digital transformation for leading organizations across various industries, and grow the ML practice within a scaling organization.
• Collaborative culture that values innovation, responsibility, and technical excellence.
• Comprehensive benefits include health, dental, and vision insurance, 401(k) with company match, and generous PTO.
• Ongoing professional development and training opportunities in AI, data science, and cloud technologies.
• A collaborative and innovative work environment with access to top-tier data and AI/ML engineers.
• At Provectus, we are committed to diversity, equity, and inclusion.