Staff Software Engineer, Machine Learning

Company:  owl.co
Location: New York County
Closing Date: 04/06/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
*We are not working with recruitment agencies at this time*

enables insurers to fight illegitimate claims at scale while removing human bias from the process. Our clients are the top insurance companies across North America and are getting incredible results through our AI-powered evidence-based platform. We are on a mission to bring state-of-the-art ML and NLP methods to transform this traditionally manual activity into an equitable process. We are and have engineering offices in New York City, Toronto, and Vancouver.

We are actively seeking a highly motivated and experienced Senior Software Engineer, with a strong focus on machine learning and natural language processing (NLP) to drive the development of the core intelligence underlying our innovative products. In this role, you will collaborate closely with various teams, leading the design, implementation, and production of some of the most impactful systems in the insurance industry.

What You Will Be Doing:

Collaborate with cross-functional teams to design, implement, and enhance machine learning-powered systems and products, with a specific emphasis on NLP.

Develop and maintain advanced NLP models for document classification, ranking, and annotation, serving as the core intelligence of our products.

Work closely with internal stakeholders to conduct data analyses that address customer needs and generate actionable insights, leveraging NLP techniques.

Design and execute experiments aimed at improving internal processes, enhancing data collection, and refining ML models, with a strong NLP component.

Lead technical discussions and contribute to key technical decisions within the team, especially as they relate to software engineering aspects of NLP strategies.

Develop clean, well-documented, and maintainable code spanning the entire technology stack, with a strong focus on NLP implementation and software engineering best practices.

Mentor junior engineers, supporting their growth and development within the context of NLP software engineering.

Analyze user behavior on our platform to uncover new features, trends, and insights that can enhance our products, using NLP-driven analytics.

Contribute to the evolution and direction of our analytics practices, particularly in the realm of NLP-driven software engineering.

Requirements:

Possess a minimum of 4 years of hands-on experience in software engineering with a strong portfolio of applied projects in the industry, with a significant focus on NLP.

Hold an advanced degree or equivalent qualification, ideally in a field related to NLP, machine learning, or software engineering.

Exhibit extensive proficiency in Python, particularly for NLP-related software engineering tasks.

Demonstrate expertise in software engineering practices, including code quality, maintainability, and scalability, with a strong emphasis on NLP-driven software solutions.

Be proficient in common data science tools and query languages, including pandas, NumPy, seaborn, scikit-learn, and SQL, with a focus on NLP data analysis from a software engineering perspective.

Possess strong interpersonal and written communication skills, along with expertise in A/B testing, statistical analysis, and applied ML theory and practice, especially in the context of software engineering.

Familiarity with AWS data services, such as Glue, Athena, QuickSight, and related technologies, and their application to NLP-driven software engineering tasks.

Benefits

Medical: 100% paid medical, dental, vision

Pension: 401K matching

Short & long-term disability

Recharge: 4 weeks of paid time off, 10 public holidays, additional sick days, and time off over the winter holidays

Personal development: $1,200/year towards your fitness expenses, favorite activities, or professional development

Hybrid working environment

Please note that we can not provide visa sponsorship at this time.

Apply Now
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