Machine Learning Research Engineer - Remote Eligible

Machine Learning Research Engineer

LaSalle Network is partnering with an innovative technology company to identify a Machine Learning Research Engineer. This role offers the opportunity to design, build, and deploy high-performance deep learning systems at scale, directly impacting platforms that handle millions of requests and events daily. As a member of the Machine Learning team, you will play a key role in developing advanced NLP and LLM-driven solutions, expanding core technology platforms, and shaping the organization's technical vision. This is a high-impact, growth-oriented role where you will work end-to-end—from problem definition through production deployment.

What You'll Do

• Develop and train deep learning models for NLP tasks, including NER, sequence classification, and language modeling using pre-trained and custom transformers.
• Design and implement LLM-driven solutions (fine-tuning, retrieval-augmented generation, agentic patterns, etc.).
• Build and maintain systems, APIs, and data pipelines to deliver machine learning insights across multiple products and platforms.
• Collaborate with ML research engineers, MLOps engineers, product managers, and cross-functional teams, owning projects from inception through delivery.
• Contribute to technical vision and strategy, proposing and driving organization-wide initiatives in machine learning.

What You'll Bring

• 2+ years of experience building and deploying ML models and APIs in production (preferably cloud-based environments such as AWS or GCP).
• Strong foundation in deep learning modeling and production-quality pipelines for NLP, computer vision, or information retrieval.
• Hands-on experience with LLMs (RAG, evaluation frameworks, agentic patterns, retrieval methods).
• Proficiency with Python, PyTorch, and Hugging Face transformers.
• Knowledge of modern NLP algorithms and methods (transformers, embeddings, attention models, information retrieval).
• Strong software engineering, debugging, and performance optimization skills.
• Master's or PhD in Machine Learning, Computer Science, Mathematics, Statistics, or related field, OR 3+ years of equivalent industry experience.

Nice to Haves

• Experience selecting and evaluating ML approaches and clearly communicating tradeoffs.
• Familiarity with model inference optimization tools (TensorRT, ONNX, TorchScript, vLLM, etc.).
• Understanding of software design patterns (REST, MVC, auto-scaling).
• Experience supporting multi-language machine learning solutions.

Thanks, Griffin Taylor Project Manager LaSalle Network