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Jobs or company...

Machine Learning Ops Engineer (100% REMOTE/NO C2C)

Salary undisclosed

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Dice
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Our client, a US Fortune 250 company and a global Medical technology corporation serving customers in Clinical Labs, Health care research & Pharmaceutical industry, seeks an Machine Learning Ops Engineer

_______________________________________________

NOTE: THIS IS 100% REMOTE ROLE & ONLY W2 CANDIDATES (NO C2C/1099)

*** Candidate must be authorized to work in USA without requiring sponsorship ***

Position: Machine Learning Ops Engineer (Job ID: CFNJP00049801)

Location: San Diego CA 92130 (100% REMOTE)

Duration: 10 Months + Strong Possibility of Extension

____________________________________________________________________________

We're seeking an experienced MLOps Engineer to lead the operationalization of our Machine Learning workloads. As a key team member, you'll be responsible for designing, building, and maintaining infrastructure required for efficient development, deployment, and monitoring of machine learning workloads. Your close collaboration with data scientists will ensure that our models are reliable, scalable, and performing optimally. This role requires expertise in automating ML workflows, enhancing model reproducibility, and ensuring continuous integration and delivery.

Responsibilities:

  • Architect for scalable, cost-efficient, reliable and secure ML solution.
  • Design, implement and deploy ML solutions in AWS.
  • Select and justify appropriate ML technology within AWS and Identify appropriate AWS services to implement ML solutions.
  • Design, build, and maintain infrastructure required for efficient development, deployment, and monitoring of machine learning models.
  • Implement CI/CD pipelines for machine learning applications to ensure smooth development and deployment processes.
  • Collaborate with data scientists to understand and implement requirements for model serving, versioning, and reproducibility.
  • Monitor and optimize model performance in production, identifying and resolving issues proactively to ensure optimal results.
  • Automate repetitive tasks to improve efficiency and reduce the risk of human error in MLOps workflows.
  • Maintain documentation and provide training to team members on MLOps best practices, ensuring knowledge sharing and collaboration within the team.
  • Stay updated with the latest developments in MLOps tools, technologies, and methodologies to remain current and effective in your role.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • AWS Certified Machine Learning Specialty
  • 3+ years of experience in MLOps, DevOps, or related fields.
  • Strong programming skills in Python, GoLang with experience in other languages such as Java, C++, or Scala being a plus.
  • Experience with ML frameworks such as TensorFlow, PyTorch, and/or scikit-learn.
  • Proficiency with CI/CD tools such as Github Actions.
  • Hands-on experience with AWS.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Knowledge of infrastructure-as-code tools such as AWS CDK and Cloudformation.
  • Strong understanding of machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
  • Excellent problem-solving skills and the ability to work independently as well as part of a team.
  • Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

  • Experience with feature stores, model registries, and monitoring tools such as MLflow, Tecton, or Seldon.
  • Familiarity with data engineering tools such as AWS EMR, Glue and Apache Spark.
  • Knowledge of security best practices for machine learning systems.
  • Experience with A/B testing and model performance monitoring.

________________________________________________

If you're looking for rewarding employment and a company that puts its employees first, we'd like to work with you. We're driven, people driven.

Bhupesh Khurana

Senior Technical Recruiter

Email:

Amerit Consulting is an extremely fast-growing staffing and consulting firm. Amerit Consulting was founded in 2002 to provide consulting, temporary staffing, direct hire, and payrolling services to Fortune 500 companies nationally; as well as small to mid-sized organizations on a local & regional level. Currently, Amerit has over 2,000 employees in 47 states. We develop and implement solutions that help our clients operate more efficiently, deliver greater customer satisfaction, and see a positive impact on their bottom line. We create value by bringing together the right people to achieve results. Our clients and employees say they choose to work with Amerit because of how we work with them - with service that exceeds their expectations and a personal commitment to their success. Our deep expertise in human capital management has fueled our expansion into direct hire placements, temporary staffing, contract placements, and additional staffing and consulting services that propel our clients businesses forward.

Amerit Consulting provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Applicants, with criminal histories, are considered in a manner that is consistent with local, state and federal laws.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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