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Staff/ Principal Machine Learning (AI) Engineer

We are seeking a Principal / Staff Machine Learning Engineer to lead the design and evolution of large-scale ML and LLM systems. In this role, you will define the architectural vision, build resilient ML infrastructure, and mentor engineers while partnering closely with the delivery, data teams, and engineering leaders. You will also play a pivotal role in customer-facing engagements, presales activities, and growing the ML practice. Your impact will shape our AI capabilities.


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.


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Stepan Pushkarev
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$195000 / YEARLY (est.)
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$150000K
$240000K

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Full-time, hybrid
DATE POSTED
September 3, 2025
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