Machine Learning 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 such as Azure and Snowflake.

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

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

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

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

• Facilitate 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 establish and uphold innovative machine learning solutions.

• Apply Agile methodologies to manage project delivery, contribute to planning, and ensure the successful deployment of ML products.

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

• Stay abreast of emerging MLOps tools, cloud technologies, and best practices to guarantee solutions are scalable, secure, and appropriate for the intended purpose.

⛳️ Requirements

• A 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.

• Strong grasp of machine learning concepts, model lifecycle management, and familiarity with model management capabilities such as model definitions, performance management, and integration.

• Experience in executing model deployment, monitoring, profiling, governance, and analysis initiatives.

• Excellent communication skills, both verbal and written; ability to convey ideas and concepts effectively; capable of writing reports, business correspondence, project plans, and procedure documents.

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

• Substantial experience and understanding of cloud architecture and design (AWS, Azure, GCP).

• Familiarity with modern methods for automating machine learning pipelines.

• Knowledge of Agile and Waterfall methodologies.

• Ability to independently manage multiple task assignments within a structured implementation framework.

• Committed to continuous improvement and innovation.

• Self-motivated individual who works effectively with minimal oversight.

• Experience working across various teams and technologies is essential.

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

• Preferred but not required: Familiarity 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 that offers flexibility to work from anywhere.

• Enjoy team-building activities and regular social outings.

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

• Competitive salary and benefits package.