Senior NLP & ML Scientist — End-to-End Deployment

What We Do

We are looking for a Senior Data Scientist to build and deploy Natural Language processing (NLP) models utilizing a variety of Machine learning and deep learning techniques. The role will present opportunities to work on large datasets and the ability to use innovative techniques in Artificial Intelligence ranging from various NLP methods, computer vision, and deep learning to enable solutions that will be directly impactful to our customers.

What You'll Do:

• Perform exploratory analysis, construct data pipelines, build machine learning & deep-learning models end-to-end from POC to deployment for large scale production systems.
• Monitor, maintain, optimize and continuously improve the deployed machine learning solutions during day-to-day operations.
• Deploy models through docker containers on AWS/GCP/Azure that serve real time and batch prediction results for various business functions.
• Design and implement scalable models with continuous monitoring and feedback collection system to enable automatic model training.
• Optimize model and data performance in terms of reduced computation time and cost.

Knowledge and

Skills Required:

• PhD in quantitative field such as Mathematics, Statistics, Computer Science with 2+ years related work experience / MS with 5+ years of related work experience.
• Extensive experience developing end-to-end machine learning solutions and leading solution diagnosis, including designing & architecting machine learning models that solve business problems & fit into the overall engineering framework, experimentation, model pipeline build, performance optimization, integration and deployment.
• Proficiency in machine learning, NLP & deep learning techniques for tasks involving Named Entity Recognition, document/sentence embeddings, classification.
• Proficiency with programming languages such as Python & SQL as well as toolkits/frameworks including spaCy, gensim, PyTorch/Tensorflow.
• Strong experience in building end-to-end data pipelines, model performance monitoring processes and continuous model delivery. Knowledge of AWS Lambda, AWS Glue is a big plus.
• Familiarity with MLOps & common MLOps toolkits, e.g. MLflow, Sagemaker.
• Knowledge and experience working with engineering toolkits that are frequently used with machine learning model deployment. e.g., Git, Git Hub Actions, Docker, AWS EC2, AWS ECS, AWS ECR etc.
• Familiarity with large scale data processing techniques & tools, e.g., multi-threaded computing, GPU computing, distributed computing in Ray, PySpark, etc.

Pay Range: $ 143,000 - $195,000 annually

This hiring range is a good faith and reasonable estimate of the salary range of possible compensation at the time of the posting and is subject to change. The actual compensation offered will be determined by various factors, which may include a candidate’s education, training, experience, and geographic location.

What We Offer

By choice, we don’t simply accept individuality – we embrace it, we support it, and we thrive on it! Our People First Culture celebrates diversity, equity and inclusion not simply because it’s the right thing to do, but also because it’s the key to our success. We are proud to foster an authentic and inclusive workplace For All. You are free and encouraged to bring your entire, unique self to work.

First American is an equal opportunity employer in every sense of the term.