Machine Learning Engineer

Your Role: Develop & Optimize novel ML Models– Work with real world data, design and benchmark ML experiments, and communicate insights that drive improvements Engineer: You’ll develop and refine ML pipelines, ensure reproducibility and scalability, and assist in integration and deployment. Researcher: You’ll conduct advanced experiments, test new ideas, and produce actionable insights for the Research team to incorporate into the core model Benchmark & Experiment– Conduct rigorous benchmarking, performance evaluations, and model optimization to push the limits of ML performance. Collaboration & Execution- Collaborate with researchers, stakeholders, and client-facing teams to ensure alignment on project requirements. Deploy Scalable AI Systems– Build production-ready ML that integrate seamlessly into real-world applications. RequirementsEducation- Bachelor’s or Master’s in a related field 3-7 years of experience Proven experience indeveloping and deploying MLmodels at scale. Times Series ML techniques– Some of: Neural Networks, Probabilistic Models, gen AI, Active Learning, Reinforcement Learning Python ML frameworks(PyTorch, JAX, Tensorflow) anddeep learning industry developments Strong understanding ofML fundamentals(regression, classification, clustering, performance metrics) and scikit-learn. Quantum Enthusiasm– A background in quantum mechanics, complex linear algebra, or an interest in applying quantum concepts to ML is a strong plus. Cloud(AWS, Azure or GCP) Applied Research Skills– Ability to design experiments, analyze performance metrics, and iterate rapidly. Collaborative & Impact-Driven– Comfortable working in cross-functional teams, translating research insights into practical AI solutions. Ready to Shape the Future? If you’re excited about working on a new ML paradigm that’s transforming multiple high-impact sectors, apply now!