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TAKE YOUR CAREER TO NEW HEIGHTS WITH LOOPIO! 🚀✨ We are seeking a highly skilled Senior Machine Learning Engineer with deep expertise in NLP, large language models, and model deployment. This role focuses on building and operationalizing the core ML components that power our next generation search, summarization, and answer generation capabilities. You will work closely with Applied Scientists, Product, and Engineering to bring advanced models from prototype to reliable, scalable production systems. This role requires close collaboration with teams across Canada, the UK, and India. To accommodate the time zone differences, you will be expected to work from [11 am - 7:30 pm IST]. 💻 What You’ll Be Doing Advanced Modeling & Applied Science - Build and productionize LLM and NLP models across retrieval, summarization, classification, and generative tasks by developing optimized embedding pipelines, prompt strategies, and fine tuning methods while translating experimental prototypes into robust components that consistently perform under production conditions. - Improve model accuracy, relevance, and robustness through structured evaluation frameworks, systematic error analysis, and iterative experimentation that ensures predictable behavior over time. System Architecture & Engineering - Design and implement scalable ML services and inference pipelines in Python using modern ML frameworks, incorporating efficient serving strategies such as batching, caching, streaming, and performance tuned deployment patterns that meet latency, reliability, and throughput requirements. - Integrate models with retrieval systems, feature stores, and knowledge sources while applying strong engineering discipline in automated testing, observability, logging, and operational readiness to support durable, maintainable ML systems. - Contribute to core architectural decisions that balance modeling complexity with performance, maintainability, and long term extensibility. Delivery, Collaboration & Leadership - Translate complex NLP and LLM product requirements into structured engineering plans with clear milestones while collaborating closely with Product, Engineering, and Applied Science partners to align expectations, remove constraints, and deliver measurable customer impact. - Participate in technical design reviews and champion improvements in ML engineering practices including deployment standards, model QA, code quality, and operational excellence while providing informal mentorship on modern NLP techniques and scalable model serving. - Demonstrate strong ownership and attention to detail by driving high quality delivery in a fast moving environment focused on reliability, clarity, and meaningful outcomes. ✨ What You’ll Bring to the Team Proven Expertise in Machine Learning, Language Models, and NLP - 4+ years applying ML in production with practical depth in NLP, LLM workflows, embeddings, or retrieval augmented systems. - Hands on and deep experience with transformer models, embedding based methods, and retrieval augmented techniques, prompt structured or fine tuned LLMs, for reasoning and generation tasks. - Ability to turn prototypes into stable engineering solutions that perform consistently in production environments. System Design, Scalability, and Software Engineering Rigor - Strong proficiency in Python, modern ML frameworks such as PyTorch or TensorFlow, and API or microservice development. - Experience building scalable and reliable ML services with attention to latency, observability, testing, deployment patterns, and runtime durability. - Ability to design robust agentic components including control flow, state management, and integrations with retrieval and knowledge systems. Business and Product Acumen - Ability to frame technical decisions in terms of customer impact, product value, and measurable improvements to workflow efficiency or answer quality. - Strong collabora