Lead Machine Learning Engineer, Corporate Vice President

Key Skills

Aartificial intelligence, Amazon RedShift, Data science techniques, Data structuring, Generative AI, Keras software library, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Natural Language Toolkit - NLTK, Postgres, PyTorch, Snowflake, spaCy, SQL, TensorFlow

Job Description

The Center for Data Science and Artificial Intelligence (CDSAi) is an innovative corporate Analytics group within New York Life. We are a rapidly growing entrepreneurial department which aims to design, create and offer innovative data-driven solutions for many parts of the enterprise. We are aided by New York Life’s existing business with a large market share in individual life insurance. We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a whole new generation of predictive analytics and artificial intelligence solutions.

In fact, we are building one of the first multivariate model-based continuous risk differentiations in the industry. We are also working on models for differentiated advertising allocation by geography, channel and segment. Geographic analytics on agents and customers, application fraud detection, agent success prediction and client prospecting analytics (off-line and on-line) are other exciting examples of enormous incremental value from analytics. Our products are implemented into real-time core business processes and decisions that drive the company (e.g. ,underwriting, pricing, agent recruiting, prospecting, advertising allocation, new product development).

We work with data ranging from demographics, credit and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. We have a modern computing environment with a solid suite of data science/modeling tools and packages, and a large (but manageable) group of well-trained professionals at various levels to support you. Life insurance is on the verge of huge change. This is a chance to drive the transformation of an industry.

The Center for Data Science and Artificial Intelligence (CDSAi) is the 60-person innovative corporate Data Science group within New York Life, led by Chief Analytics Officer Glenn Hofmann (https://www.linkedin.com/in/glennhofmann/). We are a rapidly growing entrepreneurial department which designs, creates, and deploys innovative data-driven solutions for many parts of the enterprise. For more opportunities in data science, please visit our website (https://www.newyorklife.com/careers/corporate/data-science)

You will work with Data Scientists and MLOps Engineers to apply software engineering best practices to the Model Development Lifecycle (MDLC). You will help set ML engineering standards/practices as well as oversee others’ work. You’ll be an instrumental member of the MLOps team lead by Boris Simanovich (https://www.linkedin.com/in/boris-simanovich/)

Responsibilities

1. Responsible for design and development of production grade Machine Learning solutions
2. Ensuring all ML code conforms to software engineering best practices and coding standards
3. Help set ML engineering standards (development stack, sample starter projects, etc.)
4. Implementation of models with debugging, scaling and monitoring in mind
5. Mentor engineers and data scientists in applying software engineering to ML problems

1. Help set up ML experiments for server-based hyperparameter tuning
2. Work with MLOps Engineers to develop pipelines and tools to automate model deployment
3. Mentor ML Engineers and Data Scientists in proper development practices via Pull Requests
4. Collaborate with the team on architecture and implementation
5. Expertise in developing solution architectures that integrate ML models into real-world systems
6. Hands-on prototyping of new technology and AI solutions
7. Collaborate with product managers, data scientists and other engineers
8. Review code to ensure solutions are properly designed and implemented
9. Stay up to date with the latest AI trends/emerging technologies and look for opportunities to improve the stack
10. Current understanding of LLMs and their use
11. Effectively articulate information and ideas to a diverse group of people

Required qualifications

• 7+ years of experience in Lead Software Engineering position with at least 3-years hands on with implementing AI/ML solutions
• Expert in Python, including experience with machine learning libraries and frameworks such as sklearn, TensorFlow, PyTorch, or Keras
• Understanding of containerization (Docker & Linux experience)
• Experience optimizing/tuning models
• Understanding of GPU acceleration techniques
• Passionate about technology transformations, innovation, and continuous improvement
• Experience with advanced natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face
• Strong knowledge of data structures, algorithms, and software engineering principles
• Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake
• Experience with cloud compute environments (AWS) along with cloud-native tools
• Experience with Agile/Scrum methodology and best practices
• Graduate-level degree in computer science, engineering, or relevant work experience

Preferred: 

• Previous work experience with Generative AI
• Understanding of use and implementation of Vector Databases
• Kubernetes container orchestration experience
• Insurance industry experience