ML Ops Engineer

Job Type: Full-time Experience: 4 to 8 years Job Description: Analyzing, designing, developing, and managing the infrastructure to release scalable Data Science models. The ML Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated, and repeatable way. Key Responsibilities: Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to the user requests in near real time. Design and implement the pipelines for training and deployment of ML models. Design dashboards to monitor a system. Collect metrics and create alerts based on them. Design and execute performance tests. Perform feasibility studies/analysis with a critical point of view. Support and maintain (troubleshoot issues with data and applications). Develop technical documentation for applications, including diagrams and manuals. Working on many different software challenges always ensuring a combination of simplicity and maintainability within the code. Contribute to architectural designs of large complexity and size, potentially involving several distinct software components. Mentoring other engineers fostering good engineering practices across the department. Working closely with data scientists and a variety of end-users (across diverse cultures) to ensure technical compatibility and user satisfaction. Work as a member of a team, encouraging team building, motivation and cultivating effective team relations. Role Requirements E=essential, P=preferred: E Bachelor s degree in Computer Science or related field. P Master s degree in data engineering or related field. E Demonstrated experience and knowledge in Linux and Docker containers. E Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS). P Demonstrated experience and knowledge in distributed systems. E Proficient in programming languages: Python. P Experience with ML/Ops technologies like Azure ML. E Self driving and good communication skills. P Experience with AI/ML frameworks: Torch, Onyx, TensorFlow. E Experience designing and implementing CICD pipelines for automation. P Experience designing monitoring dashboards (Grafana or similar). P Experience with container orchestrators (Kubernetes, Docker Swarm). E Experience in using collaborative developing tools such as Git, Confluence, Jira, etc. Key Traits : Should have excellent communication skills. Should be self motivated and willing to work as part of a team. Should be able to collaborate and coordinate with offshore and onshore teams. Be a problem solver and be proactive to solve the challenges that come his/her way. Company Profile: Blackstraw.ai is an end-to-end technology services company specializing in Artificial Intelligence (AI) and Engineering solutions across Data Science, Data Engineering, LLM/GenAI and LLMOps. Founded in 2018, we help global enterprises across North America, Europe and Asia to build and operationalize AI systems that create measurable business impact. Our mission is to make AI adoption simpler, faster and scalable through a blend of deep domain expertise, reusable accelerators and proven engineering practices. With a 450+ strong team of engineers, data scientists and AI specialists, we partner with organizations to deliver real-world outcomes in areas such as predictive analytics, computer vision, natural language processing and Generative AI. At Blackstraw.ai, we re passionate about solving complex business challenges through intelligent automation, modern data architectures and next-gen AI applications enabling enterprises to move from AI experimentation to transformation. Headquartered in Florida (USA) with operations in Canada and India, Blackstraw.ai continues to empower global enterprises to unlock the true potential of AI. Disclaimer :This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.