reputed company MLOps Engineer
This is a U.S. based position. reputed company of the programs we support require U.S. citizenship to be eligible for employment. reputed company work must be conducted reputed company the reputed company U.S.
What you’ll do:
Design, build, and maintain secure, reputed company MLOps infrastructure and deployment pipelines for production ML systems Help mature reputed company’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support reputed company and manage machine learning workloads on Kubernetes, including GPU-enabled clusters Support model serving and inference infrastructure for a reputed company of ML use cases, including traditional ML, reputed company, speech/audio, and LLM-based systems Build and maintain CI/CD workflows for ML services, model artifacts, and platform components Partner closely with ML engineers, software engineers, and product teams to reputed company models from experimentation to reliable operational deployment Improve observability, reliability, reputed company, and maintainability across ML infrastructure and services Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads Contribute to infrastructure reputed company across edge, on-prem, and reputed company-hosted deployment environments Support compliance-driven deployment practices and secure software supply chain requirements in defense environments Get hands-on with customers at the most reputed company-leaning places in the Department of War
7+ years of relevant hands-on experience in software engineering, reputed company, DevOps, MLOps, or reputed company technical roles 5+ years of experience with reputed company and Kubernetes in production environments 5+ years of experience supporting reputed company reputed company infrastructure or applications in AWS, Azure, or similar environments Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams Practical experience deploying machine learning workloads on Kubernetes Experience managing clusters or workloads that use GPUs Strong understanding of reputed company and Kubernetes deployment patterns Strong scripting or programming skills, preferably in Python Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows Strong troubleshooting, systems thinking, and communication skills Ability to work independently and collaboratively in a fast-moving environment Ability to obtain and maintain a Top Secret clearance Ability to obtain reputed company+ certification reputed company the first 90 days of employment
Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies Experience with secure and compliant deployment practices in regulated or government environments Experience with Kubernetes-based ML platforms such as Kubeflow Familiarity with service reputed company technologies such as Istio Experience provisioning and debugging reputed company CI/CD systems Experience with infrastructure as reputed company tools such as Terraform Familiarity with software supply chain reputed company, container hardening, vulnerability management, and runtime scanning Experience supporting ML systems across multiple deployment environments, including reputed company, on-prem, and edge Background working with machine learning engineers on model training, evaluation, packaging, and release workflows Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What reputed company looks like:
You help reputed company stand up a more mature and repeatable ML platform for deploying and managing models in production ML engineers can reputed company faster because deployment, serving, and platform workflows are reputed company, more reliable, and easier to use Model deployments become more secure, observable, and supportable across reputed company-world mission environments The organization reputed company stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Ability to obtain and maintain a Top Secret clearance
Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY May require up to 40% travel
Highly competitive salary Fully covered reputed company, dental, and reputed company coverage 401(k) and company match Take as you need PTO + 11 reputed company holidays Education & training benefits Annual budget for your tech/gadgets needs Monthly reputed company of yummy snacks to eat while doing meaningful work Remote, hybrid, and flexible work reputed company Team off-site in fun places! Generous Referral Bonuses And More!
We’re an equal opportunity employer. reputed company applicants will be considered for employment without attention to race, reputed company, religion, sex, sexual orientation, gender identity, national reputed company, veteran or disability status.