Senior ML Engineer — Remote (US East) & Indy Hybrid

Workana; Indianapolis (IN); Hybrid; USD 130,000 - 210,000; Full time

Benefits offered by this job

Travel reimbursement

Flexible work arrangements

Career growth

Long-term contractor

Job summary

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

Qualifications

• Proven experience building production-grade ML systems.
• Strong Python and ML engineering practices.
• Experience deploying ML models at scale in production.
• Knowledge of microservices and cloud-native workflows.
• Ability to turn research models into production services.

Responsibilities

• Own ML system architecture and production pipelines.
• Transition models from research to scalable services.
• Design training, inference, evaluation, and deployment pipelines.
• Integrate models into APIs, backends, and core workflows.
• Optimize for latency, throughput, scalability, reliability and cost.
• Set engineering standards for versioning, testing and observability.
• Collaborate with domain experts, data scientists, and teams.
• Diagnose and resolve bottlenecks across the ML stack.

Skills

Architecture

Production systems

ML pipelines

Python

Cloud-native

Observability

Collaboration

Problem-solving

Job description

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