Provectus

Staff/Principal Machine Learning Engineer, AI

Provectus

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Lead

Tech Stack

AirflowAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchSparkTensorflow

About the role

  • 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
  • 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
  • Engage with clients and prospects in presales cycles to understand needs, design tailored ML/AI and Data solutions, and demonstrate technical feasibility
  • Collaborate with sales and business development to create proposals, proofs of concept, and technical presentations
  • Act as a trusted advisor on Data/ML adoption and infrastructure strategy
  • Grow and mature the ML practice by developing methodologies, frameworks, and reusable assets
  • Represent the company at industry events, conferences, and client workshops as a thought leader in ML and AI

Requirements

  • 7–10+ years of experience in Machine Learning Engineering
  • 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