Software Engineer – ML Engineering/Mlops

Software Engineer – ML Engineering/Mlops

Requirements

• Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field.
• 2+ years of relevant job experience
• Strong foundation in software engineering principles and practices, with proficiency in at least one programming language (e.g., Python, C++).
• Understanding of data structures, algorithms, and software design principles.
• Strong problem-solving skills and the ability to work independently as well as collaboratively in a team environment.
• Excellent communication and interpersonal skills.
• Familiarity with machine learning concepts and frameworks (e.g., PyTorch, scikit-learn).
• Experience with machine learning model deployment techniques.
• Experience with cloud services (AWS, GCP, Azure)
• Knowledge of containerization technologies (e.g., Docker)

Responsibilities

• Partner cross-functionally with Research/Engineering/Clinical to productize early-stage algorithm prototypes.
• Develop robust algorithm development pipelines, such as automated training and evaluation routines.
• Define and implement software and algorithm validation strategies.
• Deploy and monitor algorithms in a Production environment.
• Contribute to our internal algorithm training and data platforms.

Preferred Qualifications

• Experience with CI/CD pipelines and related tools (e.g., Jenkins, Github Actions).
• Experience with data warehouses (e.g., Redshift / Snowflake / Databricks).
• Experience with distributed computing frameworks (e.g., Ray/Spark/Dask).
• A keen interest in staying up-to-date with the latest trends and advancements in machine learning, artificial intelligence, and distributed computing.
• Demonstrated initiative and creativity in solving complex problems.
• Blog (or other media) communicating the candidate’s data science or engineering projects, ideas, or first-principles thinking.