> Markdown version of [/jobs/ext/3114969-senior-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3114969-senior-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior ML Engineer - **Company:** WORK ANYWHERE NOW LLC - **Location:** Indianapolis, IN, United States (Remote available) - **Experience:** Expert - **Salary:** $122,741.0 - $199,454.0 - **Contract:** Contract - **Skills:** Application Programming Interfaces (APIs), Computing Platforms, Cloud Engineering, Python (Programming Language), Machine Learning, Software Engineering, Software Systems, Delivery Pipeline, Backend, Build Management, Low Latency, Machine Learning Operations, Microservices - **Published:** September 27, 2026 - **Apply:** https://www.careerjet.com/jobad/usd93ebe551be988dfbd344f7002df0229 ## About the Role * 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. ## Description 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. Selection Process The process consists of 3 stages: * Initial interview with Workana's recruiting team. * People interview with the client's team. * Technical Interview with the client's team (rapid fire style). 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. 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. ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)