Senior MLOps Engineer
Proxify- Posted : 2 months ago
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.
Skills
- php
- symfony
- docker
- javascript
- mysql
