Senior Software Engineer I, ML Ops

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Job Overview

As a Senior Software Engineer I, ML Ops at Generate:Biomedicines, you will play a pivotal role in developing and implementing machine learning operations that support our innovative biomedicine initiatives. You will collaborate closely with data scientists and software engineers to optimize end-to-end ML workflows, ensuring that our models are efficiently deployed, monitored, and maintained in a production environment. This position not only demands technical expertise in software engineering but also requires a strong understanding of machine learning principles and operations, as you will be instrumental in enhancing our computational infrastructure and workflow efficiencies.

Job Responsibilities

• Design, implement, and maintain robust ML Ops frameworks that facilitate automated deployment, monitoring, and retraining of machine learning models.
• Collaborate with cross-functional teams to define requirements and translate them into scalable software solutions.
• Integrate machine learning workflows with existing software systems and databases to ensure seamless data flow.
• Develop and conduct performance testing, optimization, and troubleshooting of ML models in production.
• Train and mentor junior engineers, providing guidance on best practices in ML Ops and software development.
• Keep abreast of emerging trends and technologies in ML and data engineering to enhance our capabilities and offerings.
• Document processes, technical specifications, and architecture designs to promote knowledge sharing and system clarity.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master's degree preferred.
• Minimum of 5 years of professional experience in software engineering, with a strong focus on machine learning operations.
• Proficiency in programming languages such as Python, Java, or C++.
• Hands-on experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Deep understanding of ML model lifecycle management and deployment in cloud environments (e.g., AWS, Azure, Google Cloud).
• Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Experience with data pipeline tools and ETL processes for managing large datasets.
• Proven ability to work collaboratively in a team-oriented environment and engage with stakeholders effectively.

Technologies & Tools

In this role, you will work with a variety of technologies and tools essential for ML Ops. You will utilize cloud platforms such as AWS or Google Cloud for scaling solutions and managing infrastructure. The position requires proficiency in tools for CI/CD, with emphasis on Docker and Kubernetes for containerization and orchestration. Additionally, you will engage with data processing frameworks including Apache Spark and utilize ML libraries such as TensorFlow and PyTorch for model development. Familiarity with version control systems like Git and collaboration tools such as JIRA will also be integral to effectively contributing to projects.

Ideal Candidates

The ideal candidate for the Senior Software Engineer I, ML Ops position will be a proactive and innovative thinker, possessing a strong passion for leveraging technology to drive advancements in biomedicine. You should exhibit exceptional problem-solving abilities, with a keen attention to detail and a commitment to quality in your work. Strong collaborative skills are essential, as you will be working alongside diverse teams to achieve common goals. Adaptability to evolving technologies and a desire for continuous improvement will also distinguish you in this dynamic field. Additionally, a deep curiosity for machine learning and its applications in biomedicine will fuel your efforts to push the boundaries of what we can achieve collaboratively.