Loopio Inc. is looking for a Senior Machine Learning Engineer to build and operationalize core ML components for next-generation search, summarization, and answer generation. In this role, you will bring advanced NLP and LLM models from prototype to reliable, scalable production systems.

What You'll Do

Build and productionize LLM and NLP models across retrieval, summarization, classification, and generative tasks.
Develop optimized embedding pipelines, prompt strategies, and fine-tuning methods.
Translate experimental prototypes into robust components that perform under production conditions.
Improve model accuracy, relevance, and robustness through structured evaluation frameworks and error analysis.
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.
Integrate models with retrieval systems, feature stores, and knowledge sources.
Apply strong engineering discipline in automated testing, observability, logging, and operational readiness.
Contribute to core architectural decisions balancing modeling complexity with performance and maintainability.
Translate complex NLP and LLM product requirements into structured engineering plans.
Collaborate closely with Product, Engineering, and Applied Science partners to align expectations and deliver impact.
Participate in technical design reviews and champion improvements in ML engineering practices.
Provide informal mentorship on modern NLP techniques and scalable model serving.

What We're Looking For

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 prompting structured or fine-tuning LLMs for reasoning and generation tasks.
Ability to turn prototypes into stable engineering solutions that perform consistently in production.
Strong proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
Experience with API or microservice development.
Experience building scalable and reliable ML services with attention to latency, observability, testing, and deployment patterns.
Ability to design robust agentic components including control flow, state management, and integrations.
Ability to frame technical decisions in terms of customer impact, product value, and measurable improvements.
Strong collaboration skills with cross-functional partners.
Comfort operating with ownership and urgency in a fast-moving environment.

Technical Stack

Python
PyTorch
TensorFlow

Team & Environment

You will work closely with Applied Scientists, Product, and Engineering teams.

Benefits & Compensation

Manager provides ongoing feedback and regular 1-on-1s using Lattice.
Dedicated professional mastery allowance for learning support.
Remote work setup with MacBook laptop, monthly phone and internet subsidy, and work-from-home budget.
Supportive culture with opportunities for connection in a remote-first environment.
Participation in townhalls, AMAs, and quarterly celebrations.
Access to four active Employee Resource Groups.
Award-winning workplace.