Required Skills & Experience- 6+ years of experience in machine learning engineering with ½ of the time being within DevOps environment- Proven experience in deploying and managing ML models in production environments using Kubernetes- Strong programming skills in Python, with experience in ML libraries such as TensorFlow, PyTorch, or scikit-learn- Experience with MLOps tools such as Kubeflow, MLflow, or TFX- Proficient in DevOps tools and practices including Docker, Jenkins, and Git- Extensive experience with Kubernetes for container orchestration and management- Hands-on experience with building ADF pipelines on Azure Databricks-Any experience with supply chain data domain- Excellent problem-solving and analytical skills; strong communication and teamwork abilities; ability to work in a fast-paced and dynamic environment- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field Nice to Have Skills & Experience-Knowledge of IBP (Integrated Business Planning)- Familiarity with monitoring tools such as Prometheus and Grafana- Knowledge of infrastructure-as-code tools like Terraform or Ansible- Understanding of data engineering concepts and toolsJob DescriptionA Fortune 50 client is looking for a Senior MLOps Engineer to come join their team in support of their Integrated Business Planning program. They are needing an ML engineer that is able to deploy ML models into Kubernetes. As a MLOps Engineer, you will be responsible for designing, implementing, and maintaining scalable ML infrastructure. You will work closely with data scientists, software engineers, and IT teams to ensure seamless integration and deployment of ML models into production environments. You will also be responsible for optimizing workflows and ensuring the scalability and reliability of our systems. This role will require you to collaborate with data scientists to understand model requirements and provide technical guidance on model optimization and deployment. You will develop, test, and deploy machine learning models using appropriate frameworks and libraries, and research the industry's latest machine learning platform technologies and create quick prototypes/proof-of-concepts. You will work xlosely work with cross-functional partner teams in global settings to deliver new ML features and solutions and achieve business objectives for their IBP program. Kubernetes Orchestration is a big part of this role and we are looking for this person to help design and manage Kubernetes clusters for deploying scalable ML models and applications. In addition to, implementing Kubernetes Operators for managing ML workflows and resources. You will optimize resource utilization and ensure high availability and reliability of ML services on Kubernetes and provide technical support and training to team members on ML and DevOps practices. Document processes, workflows, and infrastructure setups for transparency and knowledge sharing. This role is remote in India; however, we are looking for someone who can work between 12:00 PM IST to 9:00 PM IST.CompensationThis role is targeting candidates at a calculated pay range between $17-$20 USD per hour.
Job Title
Insight Global | Machine Learning Engineer