[US Company] Machine Learning Platform Engineer

Our client is seeking a Machine Learning Platform Engineer to play a pivotal role in the design, implementation, and maintenance of robust machine learning platforms and data pipelines. This role offers an exciting opportunity to ensure smooth deployment, scaling, and monitoring of models in production environments. The successful candidate will drive automation to accelerate the development, evaluation, and integration of machine learning models, improving collaboration and overall efficiency.

What you'll do:

As a Machine Learning Platform Engineer, your primary responsibility will be to design, implement, and maintain robust machine learning platforms and data pipelines. You will ensure seamless deployment, scaling, and monitoring of models in production environments. Your strong programming skills will be crucial in setting up monitoring systems for deployed models and tracking key metrics. You will apply your knowledge of software engineering best practices within the context of machine learning. Your collaborative nature will be essential as you work with ML developers to ensure model performance is maintained in production. You will also work closely with software engineers to integrate ML systems into the broader application stack. Your commitment to enhancing collaboration and efficiency will shine as you accelerate machine learning development, evaluation, and integration speed through automation of workflows, tools, and processes.

• Design, implement and maintain machine learning platform and data pipelines
• Set up monitoring systems for deployed models and track key metrics
• Apply and share software engineering best practices within the context of machine learning
• Collaborate with ML developers to ensure model performance is maintained in production
• Work with software engineers to integrate ML systems into the broader application stack
• Accelerate machine learning development, evaluation, and integration speed through automation of workflows, tools, and processes

What you bring:

The ideal candidate for the ML Platform Engineer position brings strong programming skills in Python along with proficiency in containerization tools such as Docker or Kubernetes. Experience with cloud platforms like GCP, AWS or Azure is required. A background working with backend servers and APIs using frameworks like FastAPI or Django is essential. Additional experience with machine learning frameworks like PyTorch or TensorFlow, MLOps tools such as Kubeflow, MLflow or TFX, monitoring tools like Prometheus or Grafana and logging frameworks would be a significant advantage. Knowledge of data engineering concepts including ETL pipelines, data lakes, and data warehouses would also be beneficial.

• Strong programming skills in Python
• Proficiency with containerization tools (Docker, Kubernetes) and cloud platforms (GCP, AWS, Azure)
• Experience working with backend servers and APIs (e.g., FastAPI, Django)
• Experience with machine learning frameworks (PyTorch, TensorFlow) is a plus
• Experience with MLOps tools (Kubeflow, MLflow, TFX) is a plus
• Experience with monitoring tools (Prometheus, Grafana) and logging frameworks is a plus
• Knowledge of data engineering concepts (ETL pipelines, data lakes, data warehouses) is a plus

What sets this company apart:

Our client is a leading player in the tech industry, known for their commitment to innovation and excellence. They offer an inclusive and supportive work environment where every team member's contribution is valued. Their focus on collaboration and efficiency makes them a preferred employer for professionals seeking growth and development opportunities in a dynamic setting.

What's next:

Ready to take your career to the next level? Apply now!

Apply today by clicking on the link provided. We look forward to receiving your application!