Sr. Solutions Architect - Commercial

Key Skills

Celery, Docker, Natural Language Processing (NLP), Python Programming, PyTorch, RabbitMQ, Scikit-learn, spaCy

Job Description

Job Summary:

We are seeking a highly skilled and motivated Senior Solutions Architect for our Commercial Delivery team who is passionate about delivering value to Enterprise clients with Generative AI. If you have experience harnessing data to deliver mission impact at enterprise scale, enjoy working alongside product teams to iteratively improve capabilities, and thrive in client-facing technical environments, we would love to hear from you!

In this role, you will leverage your expertise in Python, Natural Language Processing (NLP) techniques, algorithms and statistics, as well as your familiarity with enterprise needs to deploy, optimize, and evaluate innovative machine learning and algorithmic solutions directly in client environments. You will need to be adept at working in a customer-facing capacity, integrating client data products into ML models in large end-user-facing system architectures, and are well-versed in tools like TensorFlow, PyTorch, Scikit-learn, and Docker.

You will collaborate closely with DevOps Engineers and Application Engineers to optimize our deployed ML solutions for clients to maximize mission impact and efficiency. You will also work closely with Applied ML Engineers in our product team to improve how users interact with ML and algorithmically driven aspects of the product. Our product team is rapidly developing and improving our product, and you’ll be a key conduit to bring customer feedback to influence our product, research, and ML deployment roadmap.

Responsibilities:

• Deploy, test, and optimize NLP models and data pipelines.
• Focus primarily on deploying algorithms and ML models using Python, Docker, and Kubernetes.
• Communicate with client and partner technical teams to maximize algorithmic impact and optimize workflows.
• Perform model tuning, prompt tuning, and other ML optimization processes alongside client technical experts to maximize the mission impact of our product.
• Participate in the delivery, evaluation, and maintenance of enterprise products, ensuring they meet high-quality standards.
• Present progress and outcomes to client non-technical leadership.
• Collaborate with Applied ML Engineers and others in our product team to address user requirements and craft features that enhance the user experience.
• Continuously improve and iterate on features to deliver mission impact.
• Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion.
• Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime.
• Stay up-to-date with the latest developments in machine learning, NLP, and related technologies, and proactively apply this knowledge to drive innovation within the company.
• This position may require travel.

Required Skills and Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, Statistics, or equivalent experience.
• Minimum 4 years of professional experience in Data Science/ML Engineering/MLOps, with a track record of delivering ML solutions..
• Strong communication skills and the ability to collaborate effectively with clients, partner vendors, end users, and cross-functional teams.
• Experience containerizing algorithms using Docker and deploying into production Kubernetes environments.
• Strong proficiency in Python and experience with NLP techniques, resources and methodologies (including but not limited to Spacy, Scikit-learn, and Pytorch).
• Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, Celery, and RabbitMQ.
• Strong coding skills with a passion for creating high-quality software and amazing user experiences.
• Ability to own ML delivery tasks end-to-end with little to no direct support.
• Comfortable supporting production systems and debugging challenges in distributed systems.
• Growth mindset with the ability to pick up new languages and technologies as required.

Please note We strongly encourage you to apply even if you don't meet all of the requirements for this role if you believe your skills and attributes may still make you a strong fit for the position.

Preferred Qualifications:

• A Masters Degree in Machine Learning, Computer Science, or related fields.
• Experience with Generative AI technologies and Large Language Models is a plus.