MLOps Engineer

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

📋 Description

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

• Develop, construct, and sustain machine learning pipelines and frameworks to cater to enterprise analytics, reporting, and product requirements.

• Engage with data science, ML engineering, data quality, and product teams to establish model deployment architecture and execution.

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

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

• Assist in enterprise-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 deploy and maintain contemporary machine learning solutions.

• Employ Agile methodologies to oversee delivery, contribute to project planning, and facilitate the successful launch of ML products.

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

• Remain updated with emerging MLOps tools, cloud technologies, and best practices to ensure solutions are scalable, secure, and purpose-fit.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field is preferred.

• A minimum of 3-7 years of pertinent experience is required.

• Demonstrated experience in machine learning engineering and operations.

• In-depth knowledge 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.

• Exceptional interpersonal, oral, and written communication skills; Ability to convey ideas and concepts effectively; capable of writing reports, business correspondence, project plans, and procedure documents.

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

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

• Familiarity with modern methods for automating machine learning pipelines.

• Knowledge of Agile and Waterfall methodologies.

• Capable of working independently and managing multiple tasks within a structured implementation framework.

• Committed to continuous improvement and innovation.

• A motivated, self-directed individual who thrives with minimal supervision.

• Must possess experience collaborating across multiple teams and technologies.

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

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

🏝️ Benefits

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

• Be part of a remote-first culture—work from anywhere with flexibility.

• Participate in team-building activities and regular outings.

• Collaborate and advance in a nurturing environment with opportunities to learn from experienced engineers.

• Competitive salary and benefits package.