Senior ML Engineer

Workana

5d • Hybrid

About The Position

Workana is seeking a Senior Machine Learning Engineer for a U.S.-based client in the life sciences and biotech domain. This role focuses on complex scientific data and machine learning systems. The ideal candidate will lead the architecture, integration, and scaling of machine learning capabilities within production-grade software systems. The position emphasizes turning models into robust, scalable, and observable production systems, rather than pure exploratory research. The role involves ownership of ML pipelines, model integration, and engineering quality, requiring a proactive professional with a great attitude to drive technical execution and collaborate with domain experts.

Requirements

• Proven track record as a Senior Machine Learning Engineer with strong software engineering fundamentals.
• Strong industry and domain knowledge within life sciences, biotech, or scientific datasets.
• Advanced proficiency in Python and modern ML/software engineering practices.
• Demonstrated experience deploying, scaling, and operating ML models in production environments.
• Deep understanding of model inference, system design, microservices, and cloud-native workflows.
• Strong collaborative mindset, excellent problem-solving ability, and a positive, proactive attitude.
• Fluent English is mandatory, as the role involves daily interaction with U.S.-based stakeholders.
• Must be based in the United States, with preference given to candidates who can work hybrid in Indianapolis, IN or travel to Indianapolis periodically.

Responsibilities

• Own the architecture and implementation of production-grade ML systems and workflows.
• Transition models from development and research into scalable production services.
• Design and build reliable training, inference, evaluation, and deployment pipelines.
• Integrate ML models into APIs, backend services, applications, and core product workflows.
• Optimize ML systems for latency, throughput, scalability, reliability, and cost-efficiency.
• Establish engineering standards for model versioning, testing, observability, and deployment.
• Collaborate closely with domain experts, data scientists, and cross-functional teams with a strong, collaborative attitude.
• Diagnose and resolve technical bottlenecks across the ML application stack.

Benefits

• Competitive salary with travel expenses covered when travel is required.
• Flexible work arrangements (Hybrid in Indianapolis, IN, or Fully Remote within the U.S. East Coast with occasional travel).
• Dynamic career growth with innovative, high-impact enterprise projects.
• Long-term independent contractor agreement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed