Senior Machine Learning Engineer

About ADA
ADA is the Data and AI Experience Company. Present in 14 markets globally, we build intelligent experiences that power enterprise growth, spanning identity and authentication, personalization, commerce, and data & AI foundations; where every touchpoint earns trust, every interaction creates value, and every decision runs on real-time intelligence, so enterprises can stay ahead and deliver measurable outcomes. Our mission is to build the worlds most intelligent growth platform for every client we serve. We work with over 1,500 global brands across CPG, Retail, Telco, BFSI, and Healthcare.
Role Overview
We are looking for a highly skilled and experienced Senior Machine Learning Engineer to join our team. In this role, you will lead the design, development, and deployment of scalable machine learning models and AI systems that solve core business problems. You will bridge the gap between complex data science concepts and robust, production-ready software engineering, acting as a technical leader and mentor within the team.
Key Responsibilities

• End-to-End ML Development: Architect, train, evaluate, and deploy machine learning models (both predictive and generative) into scalable production environments.
• MLOps & Infrastructure: Design and maintain robust ML pipelines, ensuring seamless model monitoring, versioning, automated testing, and CI/CD integration.
• Collaboration & Leadership: Partner with Data Engineers, Product Managers, and Backend Engineers to translate business requirements into technical AI solutions.
• Mentorship: Act as a technical multiplier by mentoring junior engineers, conducting code/model reviews, and championing engineering best practices.
• Innovation & Research: Stay current with the rapidly evolving AI landscape (e.g., LLMs, Agentic workflows, new architectures) and prototype state-of-the-art solutions for existing bottlenecks.
• Optimization: Fine-tune and optimize models for inference latency, throughput, and cost-efficiency at scale.
  

Required Qualifications

• Experience: 3-5 years of hands-on experience in Machine Learning, Data Science, or Software Engineering, with a proven track record of taking ML models from ideation to production.
• Education: Bachelors, Masters, or Ph.D. in Computer Science, Data Science, Mathematics, or a related quantitative field.
• Programming Languages: Deep expertise in Python and strong software engineering fundamentals (OOP, system design, data structures). Proficiency in SQL.
• ML Frameworks: Extensive experience with deep learning frameworks such as PyTorch or TensorFlow, as well as standard libraries (Scikit-Learn, Pandas, NumPy).
• Generative AI: Experience with LLMs, prompt engineering, RAG (Retrieval-Augmented Generation) architectures, and fine-tuning techniques (LoRA, PEFT).
• Deployment: Experience with containerization (Docker, Kubernetes) and model serving frameworks.
  

Preferred Qualifications (Nice To Haves)

• MLOps & Cloud: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (e.g., MLflow, Kubeflow).

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• Big Data: Familiarity with distributed computing frameworks like Spark or Ray.
• Low-Level Optimization: Experience with CUDA, model quantization, or ONNX/TensorRT for high-performance inference.
• Publications: Contributions to open-source projects or publications in top-tier AI/ML conferences.
  

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Unfortunately, we are only able to contact shortlisted applicants. We encourage you to continuously visit our website www.adaglobal.com for regular updates on available roles
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