Senior MLOps Engineer

Company

Proxify

Type

Full Time

Job Description

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. πŸ™‚

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.

Apply Now

Date Posted

02/19/2024

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