M
AI

MLOps Engineer - Remote (AWS Certified Machine Learning)

MillenniumSoft Inc · Anywhere · $106k - $109k

Actively hiring Posted 8 months ago

Position : MLOps Engineer - Remote (AWS Certified Machine Learning)

Location : San Diego, CA

Duration : 10+ Months

Total Hours/week : 40

1st Shift

Client : Medical Devices Company

Level of Experience : Senior Level

Employment Type : Contract on W2 (Need US Citizens or GC Holders or GC EAD or OPT or EAD or CPT)

Job Description

  • 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.
  • 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

  • AWS Certified Machine Learning - Specialty
  • 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.

Tags & focus areas

Used for matching and alerts on DevFound
Remote Engineer Machine Learning Aws Docker Golang Java Kubernetes Scala Tensorflow
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.