| Senior MLOps Engineer at Remote, Remote, USA |
| Email: [email protected] |
| From: Vaishnavi, Xforia [email protected] Reply to: [email protected] Looking for an ambitious, passionate and creative-minded Engineer MLOps, to support the development of MLOps, driving and enabling automated machine learning model deployments and managing the full lifecycle of our ML projects. The opportunity To play a key supporting role in shaping the overall MLOps strategy & capabilities. Building on our capabilities as sovereign cloud and HPC specialist, we bring generative AI, cybersecurity, professional and managed services expertise to enable national-scale program deployments across industries. Your key responsibilities Reporting to the Director of Engineering you will be responsible for building the foundation of our MLOps capabilities, working closely with Data Scientists, Data Engineers and multiple Technology Service departments to manage the end-to-end ML lifecycle including automation of machine learning workflows, code deployments, testing, and data validation processes. The candidate should be well-versed in using tools like Jenkins, GitLab CI, Azure DevOps, or equivalent, and should be able to integrate these tools with machine learning platforms and data repositories. Functional Design, implement, and manage CI/CD pipelines tailored for machine learning workflows. Ensure that machine learning models are properly versioned and deployed into production, staging, or testing environments automatically. Collaborate with data scientists and software engineers to optimize the automation process for training, validating, and deploying machine learning models. Continuously monitor the performance and reliability of CI/CD pipelines and make adjustments as necessary. Set up environments and fully implement scalable machine learning operations. Continuously monitor, optimize, debug and automate MLOps pipelines for increased quality and efficiencyincluding pipeline level, module level, and system-level inspection. Develop & maintain the infrastructure & tools that facilitate the deployment and monitoring of our ML algorithms in production. Keep abreast of the latest technology trends to drive standard methodologies and stay ahead of the curve. Document and track all systems, pipelines and best practices. Skills and attributes for success The measurement of your success will be based on cost savings, the impact of MLOps on business revenue, the number of projects successfully completed, improvements made to existing solutions and processes, and customer Net Promoter Score (NPS). To qualify for the role you must have 10+ years of Machine Learning Experience. Minimum of 5 years of experience in setting up and maintaining CI/CD pipelines, preferably in a machine learning context. Strong understanding of containerization and orchestration tools such as Docker and Kubernetes. Familiarity with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Proficient in scripting languages such as Python, Bash, or Shell for automation tasks. Ideally, youll also have ML Training data lifecycle. Data storage and management engines: NoSQL databases; Search engines e.g. Elasticsearch, SQL databases; Timeseries databases. Knowledge of distributed computer systems and web software development Outstanding communication and presentation skills Keywords: continuous integration continuous deployment artificial intelligence machine learning Senior MLOps Engineer [email protected] |
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| Mon Apr 01 22:26:00 UTC 2024 |