ML Operations Engineer

3 months ago

San Francisco, United States Unreal Gigs Full time
Job DescriptionJob Description

Company Overview: Welcome to the forefront of machine learning operations At our company, we're driving the next wave of AI revolution through cutting-edge ML operations technologies. Our mission is to develop scalable and reliable ML systems that empower businesses and revolutionize industries. Join us and be part of a dynamic team committed to pushing the boundaries of what's possible with MLOps.

Position Overview: As an ML Operations Engineer (MLOps), you'll play a critical role in developing and maintaining scalable and reliable machine learning pipelines and systems. Working closely with data scientists, software engineers, and DevOps specialists, you'll ensure the smooth deployment, monitoring, and optimization of machine learning models in production environments. If you're passionate about bridging the gap between data science and operations and eager to drive innovation in ML infrastructure, we want you on our team.

Requirements

Key Responsibilities:

  1. ML Pipeline Development: Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, deployment, and monitoring, leveraging best practices in MLOps.
  2. Model Deployment: Deploy machine learning models into production environments, ensuring scalability, reliability, and performance, and automating deployment processes using CI/CD pipelines.
  3. Model Monitoring: Implement monitoring and alerting systems to track model performance, data drift, and model drift, and take proactive measures to maintain model health and accuracy.
  4. Infrastructure Management: Manage cloud-based infrastructure and resources for machine learning workloads, optimizing for cost, performance, and scalability.
  5. Version Control: Implement version control and model versioning systems to track changes to models and ensure reproducibility and traceability.
  6. Collaboration and Documentation: Collaborate with cross-functional teams to define requirements, prioritize tasks, and deliver solutions that meet business objectives, and document processes and workflows for knowledge sharing and onboarding.
  7. Security and Compliance: Implement security best practices and ensure compliance with data privacy regulations in ML systems and workflows.

Qualifications:

  • Bachelor's degree or higher in Computer Science, Engineering, or related field.
  • Strong background in machine learning operations (MLOps) or DevOps, with hands-on experience in deploying and managing machine learning models in production environments.
  • Proficiency in programming languages such as Python, Java, or Go, and experience with ML frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for ML infrastructure management, such as Kubernetes, Docker, or Apache Airflow.
  • Familiarity with CI/CD pipelines, version control systems (e.g., Git), and infrastructure as code (IaC) tools (e.g., Terraform).
  • Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Benefits

  • Competitive salary: The industry standard salary for ML Operations Engineers (MLOps) typically ranges from $150,000 to $230,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
  • Comprehensive health, dental, and vision insurance plans.
  • Flexible work hours and remote work options.
  • Generous vacation and paid time off.
  • Professional development opportunities, including access to training programs, conferences, and workshops.
  • State-of-the-art technology environment with access to cutting-edge ML tools and resources.
  • Vibrant and inclusive company culture with team-building activities and social events.
  • Opportunities for career growth and advancement within the company.
  • Exciting projects with real-world impact across diverse industries.
  • Chance to work alongside top talent and industry experts in the field of ML operations.

Join Us: Ready to shape the future of ML operations? Apply now to join our team and be part of an exciting journey of innovation and growth

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