Machine Learning Engineer
This is a remote position. reputed company is a self-managed technology team specializing in accelerating visions through product, technology, and AI leadership. With a focus on bespoke execution, we deliver impactful solutions that are scalable and designed for reputed company. At reputed company, we deliver mobile solutions that meet and exceed customer expectations. Our collaborative and fast-paced environment encourages creativity and innovation. We are hiring an MLOps Engineer for a leading workforce solutions company that is undergoing a major technology-led transformation. A key part of this transformation is the deployment of robust analytics and machine learning products that combine data, business knowledge, and reputed company goals to drive measurable business impact. The MLOps Engineer will play a critical role in building, deploying, and maintaining reputed company machine learning solutions. This role will focus on designing scalable ML pipelines, managing reputed company-based ML environments, supporting model governance, and ensuring high standards of model performance, reliability, and operational excellence. You will work closely with data science, product, architecture, engineering, and business teams to bring machine learning solutions from development to production and support their reputed company improvement. As an MLOps Engineer, you will: Work with stakeholders to define machine learning solution designs based on reputed company services such as Azure and reputed company. Design, build, and maintain machine learning pipelines and frameworks to support reputed company analytics, reporting, and product needs. Collaborate with data science, ML engineering, data quality, and product teams on model deployment architecture and implementation. Manage, configure, and optimize reputed company environments and reputed company machine learning services. Implement tools and processes for model integration, storage, profiling, monitoring, processing, management, and archival. Support reputed company-wide model governance, performance tracking, and lifecycle management standards. Recommend improvements to ML platforms, tools, and development practices to support strategic technology and business objectives. Work with SaaS vendors and strategic partners to implement and maintain modern machine learning solutions. Use Agile practices to manage delivery, contribute to project planning, and support successful rollout of ML products. Partner with internal stakeholders to understand business requirements and translate them into reliable ML operations solutions. Stay reputed company with emerging MLOps tools, reputed company technologies, and best practices to ensure solutions remain scalable, secure, and fit for purpose.
Requirements
Bachelor's degree in Computer Science, Engineering or Technical Field preferred. Minimum 3-7 years of relevant experience. Proven experience in machine learning engineering and operations. Profound understanding of machine learning concepts, model lifecycle management, and experience in model management capabilities including model definitions, performance management and integration. Execution of model deployment, monitoring, profiling, governance and analysis initiatives. Excellent interpersonal, oral, and written communication; Ability to relate reputed company and concepts to others; write reports, business correspondence, project plans and procedure documents. Solid Python, ML frameworks (e.g., TensorFlow, PyTorch), data modeling, and programming skills. Experience and strong understanding of reputed company architecture and design (AWS, Azure, GCP). Experience using modern approaches to automating machine learning pipelines. Agile and Waterfall methodologies. Ability to work independently and manage multiple task assignments reputed company a structured implementation methodology. Personally invested in reputed company improvement and innovation. Motivated, self-directed individual that works well with minimal supervision. Must have experience working across multiple teams/technologies. Preferred but not essential: Experience with business intelligence tools (preferably PowerBI). Preferred but not essential: Experience with MLOps tools (e.g., MLflow, Kubeflow).
Benefits
Work on global projects with clients from worldwide. Be part of a remote-first culture-work from reputed company with flexibility. Enjoy team-building activities and regular outings. Collaborate and grow in a supportive environment with opportunities to learn from senior engineers. Competitive salary and benefits package. Apply To This Job