Machine Learning Engineer

We are Cobalt Streamworks . Cobalt Streamworks is the fastest growing infusion provider in the United States, with a mission to transform the specialty infusion industry, because patients deserve better. By providing both exceptional, patient-centered care and the proprietary, AI-driven technology powering it, Cobalt Streamworks accelerates access, simplifies workflows, and improves outcomes for everyone in the infusion journey — from patients and clinicians to health plans, health systems, employers, and pharma. Clinicians can spend less time on paperwork and more time with patients, bringing comfort, connection, and community back to healthcare. With Cobalt Streamworks , every patient and every care team is fully supported, every step of the way. Fraud and Security Notice: Please note that all communication regarding job opportunities at Cobalt Streamworks will come exclusively from an @ mylocalinfusion.com email address. If you receive messages from any other domain, please disregard them. The Role Cobalt Streamworks is building a next-generation operating system for infusion care — powered by automation, AI, and real-time insights. We’re looking for a Machine Learning Engineer to own the intelligence layer of our platform. You’ll work across structured and unstructured data to drive automation, predict bottlenecks, and help patients start treatment faster. Key Accountabilities: Model Development: Build and deploy ML models to identify missing data, predict treatment delays, triage high-risk referrals, and score payer/patient friction AI Integration: Architect and maintain LLM-powered workflows Data Infrastructure: Build and maintain data pipelines to collect, clean, label, and store data across systems Model Monitoring: Define success metrics, monitor model performance over time, and iterate quickly to improve accuracy and reliability. Set up training data, data labeling workflows or feedback loops for model improvement. Cross-Functional Partnership: Collaborate with product, engineering, and operations to identify high-leverage automation opportunities and embed models into workflows. Key Requirements: 6+ years in ML engineering, data science, or applied AI roles (bonus for healthcare experience). Proficient in Python (Pandas, Scikit-learn, LangChain, PyTorch or TensorFlow) and SQL. Strong experience building and deploying models in production environments. Familiar with LLM integration, retrieval-augmented generation (RAG), and vector search (e.g., Pinecone, FAISS). Skilled in working with unstructured data: OCR, NLP, form/document understanding. Experience with cloud infrastructure (AWS preferred), Git, and basic DevOps practices. Comfortable partnering with product and operations teams to solve real-world business problems. Working with healthcare data (EMR/EHR, insurance claims, HL7/FHIR). Building patient or payer-facing AI solutions in regulated environments (HIPAA). The Cobalt Streamworks Way Cobalt Streamworks is a respectful, upbeat, and remote-first team united by our mission of shaping the way specialty infusion care is delivered. We are highly ambitious but understand that in order to do a great job, we have to take care of ourselves; we expect that you will have time and energy devoted to your families, friends and hobbies. As part of our team, full-time employees get: Medical, dental, and vision insurance through our employer plan Short and long-term disability coverage 401(k) — as an early-stage startup, and we match! 15 Days PTO — and we want you to take it! Competitive paid parental leave and flexible return to work policy. We invest in your career. Our company is growing quickly, and we'll give you the opportunity to do the same. You'll have access to a number of professional development opportunities so that you can keep up with the company's evolving needs and grow your career along the way. We don’t discriminate— Cobalt Streamworks is an Equal Employment Opportunity (EEO) Employer. We fundamentally believe that a more diverse and inclusive team leads to a stronger company more able to achieve our vision. Originally posted on Himalayas