Machine Learning Infrastructure Engineer

As a Machine Learning Infrastructure Engineer at Songfinch, you will be responsible for developing and maintaining the critical computing infrastructure used by the ML team. Your role will involve optimizing the infrastructure to enable the extraction of value from unique data and drive cutting-edge AI capabilities in the custom music space. Working closely with the ML and Tech teams, you will contribute to the innovation of the core product, impacting both artists and customers. This is an opportunity to directly influence the future of the company and the music industry as an early hire in the ML team.

Establish, maintain and optimize our at-scale critical computing infrastructure/operations

Develop, prototype, productionize, and deploy ML applications

Monitor, update, log, alert, troubleshoot, debug ML applications

Ensure smooth, logical, transparent functionality

Continuously optimize our ML infrastructure

Proactively identify potential bottlenecks and issues, and work with the broader team(s) to resolve them

Partner with internal teams to troubleshoot and debug ML infrastructure issues

Be in-tune with the developments and advancements of ML and AI

Identify relevant trends, tools, tech, and processes that could be incorporated as potential differentiators (within infrastructure, operations, and beyond)

• B.S. in Computer Engineering, Computer Science, Electrical Engineering, Physics, Applied Math, or other relevant STEM degrees
• 3+ years of hands-on experience with relevant tech/tools
• Basics (Conda, Git, GitHub, Python)
• DevOps Tools
• Containers (Docker, etc.)
• Container Orchestration (Kubernetes, Amazon Elastic Container Service, Amazon Elastic Kubernetes Service, etc.)
• Workflow Orchestration (Apache Airflow, Flyte, AWS Step Functions, AWS Lambda, etc.)
• AWS Cloud Computing Other (Elastic Compute Cloud, S3, Sagemaker, etc.)
• MLOps tools (MLflow, AWS Sagemaker, Kubeflow, etc.)
• ML platforms/frameworks/libraries (Keras, Matplotlib, NumPy, Pandas, PyTorch/Lightning, scikit-learn, TensorFlow, etc.)
• Adaptive, collaborative, and a problem-solving mentality
• Inherent builder of things, with an insatiable curiosity / desire to continuously learn
• A strong preference for (and history of) hands-on and action-oriented execution

• Adaptive, collaborative, and problem-solving mentality
• Inherent builder of things with an insatiable curiosity/desire to continuously learn
• Strong preference for hands-on and action-oriented execution
• Strong communication skills
• Self-motivated and ignited by fast-paced environments
• Turn up the volume: doing whatever it takes to get more out of every moment, moving forward confidently, rooting for each other and celebrating wins
• Make it work: operating with an entrepreneurial spirit, turning big ideas into tactics, constantly identifying and testing new opportunities, finding solutions quickly
• Learn from every story: listening to every voice, communicating clearly, learning from diverse backgrounds, crafting thoughtful plans informed by previous wins and losses
• Power up potential: not doing egos, helping people level up instead of looking past them
• Spark happy tears: believing in the impact of what we do, looking for opportunities to make someone's day with everything we do
• Equal opportunity employer, committed to creating an inclusive and welcoming environment for every person, embracing diversity in hiring and day-to-day business.