Praxis Global Alliance - Machine Learning Engineer

About Praxis Global Alliance (Praxian Global Private Limited)

Praxis Global Alliance is an Asia-based next-generation management consulting firm making consulting practical. We help businesses adopt AI and realize business value from it. We help enterprises, investors, founders, and public sector leaders solve complex challenges and unlock superior growth, performance, and value through strategy, execution, digital, and AI-led transformation across 40+ countries.

Our teams are specialists in their practices with direct operating experience and advise clients with forward deployed capabilities in AI and Digital. Our solutions are more practical because we combine proprietary data & market intelligence, deep on-ground research network, and wide digital & AI ecosystem. Praxis works closely with enterprises, investors, founders, and public sector stakeholders to deliver industry leading business impact, and most clients find our style of management consulting 'collaborative', 'hands-on' and 'fresh'.

Praxis Solutions Help Clients

• Grow Value: We help our clients become more valuable. We partner with financial sponsors, strategic acquirers, and enterprises to formulate profit-pool driven strategy, transform business processes, conduct due diligence on investments & business plans, create and execute post-acquisition value creation blueprints.
• Grow Revenue: Our clients grow faster than competition. We help organizations accelerate growth through core business growth, expand into adjacencies, activate go-to-market strategies, develop products & channels, optimize pricing & monetization, and turn around brands.
• Grow Performance: We enable our clients to perform better. Our deep operational and execution capabilities enable us to improve productivity, unlock operational efficiencies, transform cost structures, make supply chains responsive and agile, and enhance overall business performance through hands-on transformation and execution leadership.
• Grow AI: We pioneered 'Business First AI'. We help unlock real business value from AI and Digital. Our advisory and execution weaves our AI ecosystem and 'forward deployed' teams. We help organizations prioritize and clarify their Technology and AI agenda and drive cross-functional implementation end-to-end, so clients realize the business value out of every AI and Digital initiative.
  

While we are based in Asia, our experience spans across the globe. Praxis Global Alliance has served clients in over 40 countries through a multidisciplinary team of consultants with real operating experience, AI/ML developers, data scientists and forward deployed consultants who work closely with CXOs, founders and investors to create long-term value and lasting impact. Our clients #GrowWithPraxis and find our teaming approach humble and collaborative.

Location: Mumbai, Work From Office

Experience Level: 2-4+ Years

Employment Type: Full-time

About The Role

We are looking for a seasoned Machine Learning Engineer to design, build, and deploy scalable machine learning solutions. You will play a critical role in translating business challenges into production-ready AI systems while working closely with cross-functional teams.

Key Responsibilities

• Design, develop, and deploy machine learning models at scale
• Build and maintain robust end-to-end ML pipelines (data ingestion, training, validation, deployment, monitoring)
• Collaborate with product, data, and engineering teams to solve complex business problems using ML
• Optimize models for performance, scalability, and reliability in production
• Lead feature engineering, experimentation, and model evaluation efforts
• Implement monitoring, retraining, and model lifecycle management
• Ensure adherence to best practices in ML engineering and software development
  
  

Required Skills & Qualifications

• Bachelor’s or master’s degree in computer science, Engineering, or related field
• 5+ years of experience in machine learning engineering or similar roles
• Strong programming expertise in Python
• Hands-on experience with TensorFlow, PyTorch, or Scikit-learn
• Deep understanding of ML algorithms, deep learning, and statistical techniques
• Experience with data processing tools (Pandas, NumPy, Spark)
• Proven experience deploying ML models into production (APIs, microservices)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
  
  

Preferred Qualifications

• Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow)
• Exposure to NLP, Computer Vision, or Recommendation Systems
• Experience working with large-scale distributed systems
• Knowledge of CI/CD pipelines and version control best practices

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