MLOps Engineer - Remote - USA

About FullStack

FullStack is the fastest-growing software consultancy in the Americas. We help organizations like Uber, GoDaddy, MGM, Siemens, and Stanford University build distributed software development teams, and deliver transformational digital solutions. As an employee-first company, we focus on hiring the most talented software designers and developers in the western hemisphere, by creating a positive, respectful, and supportive work environment where they can achieve their greatest potential.

We’re Most Proud Of

• Offering life-changing career opportunities to talented software professionals across the Americas.
• Building highly-skilled software development teams for hundreds of the world’s greatest companies.
• Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
• Our 4.5-star rating on GlassDoor.
• Our client Net Promoter Score of 68, twice the industry average.
  
  

The Position

We're Looking To Hire An MLOps Engineer To Join Our Team. You'll Work With Our Incredible Clients In One Of Two Ways

• Team Augmentation: You will integrate yourself directly into our client's team and work alongside their existing designers and engineers on a daily basis.
• Design & Build: You will work on a FullStack product team to build and deliver a product to our clients.
  
  

What We're Looking For

• 5 years of professional experience as a Machine Learning Engineer.
• Advanced English is required.
• Successful completion of a four-year college degree is required.
• Proven experience in implementing and managing CI/CD pipelines for ML workflows, including model training, testing, and deployment.
• Pipeline Deployment & Maintenance: Ensure daily batch predictions with efficient, error-free pipelines for ML models.
• CI/CD for ML Models: Automate ML workflows for training, testing, and deployment using CI/CD tools (GitLab CI, Jenkins, CircleCI) and containerization with Docker and Kubernetes to enhance scalability.
• Production Monitoring: Monitor and log model performance to detect decay and ensure service quality.
• Workflow Optimization: Build scalable, robust solutions for large datasets and high production loads.
• Model Versioning & Rollback: Manage versions, monitor performance, and enable rollbacks through CI/CD pipelines for seamless deployment.
• Troubleshooting: Address issues in production models to maintain reliability and performance.
• Technical Expertise: Skilled in deploying AI/ML models on cloud platforms like AWS, GCP, or Azure, with proficiency in MLOps tools such as Kubeflow, MLflow, SageMaker, and Vertex AI.
• Problem-Solving: Analyzes and enhances systems with innovative solutions.
• Data and Model Handling: Expertise in data versioning, feature stores, and model lifecycle management to ensure streamlined processes and reliability.
• Communication Skills: Strong written and verbal communication skills, enabling effective collaboration across diverse teams and stakeholders.
• Experience working on Agile / Scrum teams.
• Forensic attention to detail.
• A positive mindset and a can-do attitude.
• Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.
• Ability to consistently work 40 hours per week.
  
  

What We Offer

• Competitive Salary.
• Paid Time Off (vacation, sick leave, maternity and paternity leave, holidays).
• 100% remote work.
• The ability to work with leading startups and Fortune 500 companies.
• Health, dental, and vision insurance.
• 401(k) w/ 4% match.
• Ample opportunity for career advancement.
• Continuing education opportunities.
  
  

FullStack is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form, which can be provided upon request during our hiring and interview process.

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