Sr. Machine Learning Engineer - Hybrid schedule (10-12 onsite a month) in Los Angeles

Job DescriptionJob DescriptionWe are hiring Sr. Machine Learning Engineer - Hybrid schedule (10-12 onsite a month) for a Full Time position in Los Angeles or NYC, CA

Sr. Machine Learning Engineer

About the Role

The Senior Machine Learning Engineer is an integral part of the Technology & Information Services team. This role will be responsible for the design, deployment, and optimization of custom workflows using classical machine learning (ML), Natural Processing (NLP), and Generative AI techniques to enhance legal and business processes, while designing, building, and optimizing custom machine learning models and workflows to optimize legal and business workflows. This role will be located in our Global Services Office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence.

Responsibilities & Qualifications

Other key responsibilities include:

Contributing to the entire lifecycle of AI/ML applications including concept, design, test, release, and support

Developing and maintaining robust ML pipelines for training, validation, and model deployment

Working with DevOps or infrastructure teams to manage GPU resources, model serving frameworks, and CI/CD workflows

Evaluating and integrating new research, tools, and frameworks to advance the team s capabilities

Developing ML/GenAI solutions in a professional manner, and in accordance with established deliverable schedules and firm procedures

Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that retains

We d love to hear from you if you:

Demonstrate proficiency with Python including experience with libraries and frameworks relevant to GenAI application development (e.g., LangChain)

Exhibit proficiency with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), and serving tools (e.g., TorchServe, ONNX, Triton)

Display proficiency in training or fine-tuning models (e.g., BERT, Llama2, GPT), and their optimization (LoRA, knowledge distillation, pruning, and quantization)

And have:

A bachelor s degree and master s degree in information systems, computer science, engineering, data science, or a related field, preferably

A minimum of five (5) years of experience in industry roles focused on machine learning, applied AI, or data science

A minimum of five (5) years of Python industry experience

A minimum of three (3) years of experience working with agile teams

Experience building and productizing ML models and systems

Estimated Pay Range: 175-195K