About the Role
Loopio is seeking a highly skilled Senior Machine Learning Engineer with deep expertise in NLP, large language models, and model deployment. This role is focused 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, and you will be expected to work from 11 am - 7:30 pm IST to accommodate time zone differences.
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.
- Translate 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.
System Architecture & Engineering
- Design and implement scalable ML services and inference pipelines in Python using modern ML frameworks.
- Incorporate 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.
- Apply 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.
- Collaborate 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.
- Provide 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.
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.
- Experience with 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.
- Strong collaboration skills with cross-functional partners to align priorities and drive clear, grounded execution.
- Comfort operating with ownership and urgency in a fast-moving environment focused on delivering meaningful outcomes.