Machine Learning Operations Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Collaborate with stakeholders to establish machine learning solution designs utilizing cloud services like Azure and Snowflake.

• Create, develop, and sustain machine learning pipelines and frameworks that cater to enterprise analytics, reporting, and product requirements.

• Work alongside data science, ML engineering, data quality, and product teams to design the architecture and implementation for model deployment.

• Oversee, configure, and enhance cloud environments and associated machine learning services.

• Establish tools and processes for model integration, storage, profiling, monitoring, processing, management, and archival.

• Support organization-wide model governance, performance tracking, and lifecycle management standards.

• Suggest enhancements to ML platforms, tools, and development practices to align with strategic technology and business goals.

• Collaborate with SaaS vendors and strategic partners to implement and sustain cutting-edge machine learning solutions.

• Employ Agile practices to manage delivery, engage in project planning, and facilitate the successful launch of ML products.

• Partner with internal stakeholders to comprehend business requirements and convert them into dependable ML operations solutions.

• Keep abreast of emerging MLOps tools, cloud technologies, and best practices to ensure solutions remain scalable, secure, and fit for purpose.

⛳️ Requirements

• Preferred Bachelor's degree in Computer Science, Engineering, or a related Technical Field.

• At least 3-7 years of relevant experience.

• Demonstrable experience in machine learning engineering and operations.

• Deep understanding of machine learning concepts, model lifecycle management, and experience with model management capabilities, including model definitions, performance management, and integration.

• Proven track record in executing model deployment, monitoring, profiling, governance, and analysis initiatives.

• Excellent interpersonal, oral, and written communication skills; ability to convey ideas and concepts effectively; proficient in writing reports, business correspondence, project plans, and procedure documents.

• Strong skills in Python, ML frameworks (e.g., TensorFlow, PyTorch), data modeling, and programming.

• Experience and thorough understanding of cloud architecture and design (AWS, Azure, GCP).

• Familiarity with modern techniques for automating machine learning pipelines.

• Knowledge of Agile and Waterfall methodologies.

• Ability to work autonomously and handle multiple task assignments within a structured implementation framework.

• Committed to continuous improvement and innovation.

• Self-motivated individual who can work well with minimal supervision.

• Must have experience collaborating across various teams and technologies.

• Preferred but not mandatory: Experience with business intelligence tools (preferably PowerBI).

• Preferred but not mandatory: Experience with MLOps tools (e.g., MLflow, Kubeflow).

🏝️ Benefits

• Engage in global projects with clients from around the world.

• Enjoy a remote-first culture, allowing you to work from anywhere with flexibility.

• Participate in team-building activities and regular outings.

• Collaborate and develop in a supportive environment with opportunities to learn from experienced engineers.

• Competitive salary and benefits package.