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Workana is seeking a Senior Machine Learning Engineer for a U.S.-based life sciences client. The role emphasizes production-grade ML systems, ML pipelines, and integration with APIs and backend services. Hybrid work in Indianapolis, IN preferred, with potential for East Coast remote options.
English fluency and US-based work eligibility are required. The position focuses on turning models into scalable, observable production systems, collaborating with data scientists and domain experts across
Workana is the largest remote work platform for talent in Latin America. Our division focuses on matching exceptional professionals with leading and innovative companies around the globe.
Our client is a U.S.-based organization operating in the life sciences and biotech domain, focusing on complex scientific data and machine learning systems. They are looking for a Senior Machine Learning Engineer with deep industry domain knowledge to join their technical initiatives.
While the client prefers a hybrid schedule of 3 days a week in Indianapolis, Indiana (EDT/EST time zone), they are open to fully remote candidates across the East Coast of the U.S. who can travel to Indianapolis occasionally as needed.
As a Senior Machine Learning Engineer, you will lead the architecture, integration, and scaling of machine learning capabilities within ongoing, production-grade software systems. This role sits at the intersection of machine learning, software engineering, and platform architecture, where your primary focus will be turning models into robust, scalable, and observable production systems rather than pure exploratory research.
You will work on an ongoing project, taking ownership of ML pipelines, model integration, and engineering quality. We are seeking a proactive professional with a great attitude who can drive technical execution, collaborate with domain experts, and deliver high-impact solutions.
The process consists of 3 stages:
As Workana has multiple clients, if you pass the first round with Workana's recruiting team, you may also be considered for other relevant opportunities if the initial opportunity does not move forward.