Senior MLOps Engineer

About us:

Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂

Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 3500+ talented developers trust Proxify and its network to fulfill their dreams and objectives.

Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.

The Role:

We are looking for a Senior MLOps engineer for one of our clients. You are a perfect candidate if you are growth-oriented, you love what you do, and you enjoy working on new ideas to develop exciting products and growth features. 
 

What we’re looking for:

• Minimum of 5 years of professional experience in MLOps or a related field.

• Proven experience deploying and managing machine learning models in production environments.

• Proficiency in scripting languages (e.g., Python) and relevant MLOps tools (e.g., TensorFlow Extended, Kubeflow, MLflow).

• Experience with containerization technologies (Docker) and orchestration tools (Kubernetes).

• Strong knowledge of cloud platforms (AWS, GCP, or Azure) and their machine learning services.

• Demonstrated experience implementing automated testing, validation, and deployment processes for machine learning models.

Must-have skills:

• Python

• Azure / AWS / GCP

• Grafana / Prometheus

• SQL

Responsibilities:

• Develop and implement a comprehensive MLOps strategy, ensuring the seamless integration of machine learning models into our production environment.

• Design, build, and maintain end-to-end machine learning pipelines, encompassing data preprocessing, model training, deployment, and monitoring.

• Collaborate with cross-functional teams to design, deploy, and manage scalable infrastructure for machine learning workloads. Utilise containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, or Azure).

• Implement and manage CI/CD pipelines for machine learning models, enabling automated testing, validation, and deployment.

• Establish robust monitoring and logging systems to track the performance of machine learning models in production, ensuring timely detection of anomalies and potential issues.

• Work closely with data scientists, software engineers, and other stakeholders to understand model requirements, deployment needs, and data dependencies.

• Implement security best practices for machine learning systems and ensure compliance with relevant regulations and standards.

What Proxify offers

• Career-accelerating positions at cutting-edge companies
  Discover exclusive long-term remote engagements at the world's most interesting product companies.
   

• Hand-picked opportunities, just for you
  Skip the typical recruitment roadblocks and biases with personally matched engagements.
   

• Fast-track your independent developer career
  Start small and gain more freedom to take on new engagements as you build your independent developer career.
   

• A recruitment process that values your time
  Only one hiring process with the possibility of several positions, without any additional tests.