Director MLOps Engineering - Virginia, United States - S&P Global

Description

S&P Global

Director MLOps Engineering

Virtual ,

Virginia

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Grade/Level

(

relevant for internal applicants only

): 13

The

Location:
US, Virtual or Toronto, CA

The Team:
The Data Science COE at S&P Global in delivers AI capabilities and advancements to our Ratings products and services.

The Impact:

The Data Science COE at S&P Global is looking for a hands-on Head of Machine Learning Operations (MLOps) to lead MLOps strategy and solutions.

This role will lead, implement, and define the MLOps, LLMOps technology and platform strategy, and design and develop AI/ML/LLM/GAI technology platforms while working with a broad range of partners across data, technology and business teams.

What's in it for you:

In this role, you will play a pivotal role in leading and implementing our machine learning operations, ensuring the seamless deployment, monitoring, and management of our machine learning models and data pipelines.

As a Senior MLOps Engineering Leader, you will lead ML infrastructure initiatives, mentor junior team members, and contribute to the strategic direction of our MLOps infrastructure.

You will be instrumental in leading strategic direction for ML infrastructure in a world class AI ML team comprised of experts in AI ML modeling, ML engineers and data science and data engineering teams.

You will contribute to setting roadmaps for AI operations and be a critical part of leading S&P's AI-driven transformation to drive value internally and for our customers.

Responsibilities:

MLOps Strategy:
Develop and implement MLOps strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop roadmap and strategy for MLOps and LLMOps Platforms and model lifecycle implementation

ML Architecture Design and Development:

Responsible for the design and development of custom architecture for batch and stream processing-based AI ML pipelines including data ingestion to preprocessing to scaled AI model compute and ensure the architecture meets all SLA requirements.

Work closely with members of technology and business teams in the design, development, and implementation of Enterprise AI platform

Infrastructure Management:
Oversee the design, deployment, and management of scalable and reliable infrastructure for model training and deployment.

Model Deployment:
Lead the deployment of machine learning models into production environments, ensuring reliability and scalability.

Monitoring and Optimization:
Create and maintain robust monitoring systems to track model performance, data quality, and infrastructure health. Identify and implement optimizations to improve system efficiency.

Automation:
Develop and maintain automated pipelines for model training, testing, and deployment, optimizing for speed and reliability. Ensure CI-CD best practices are followed.

Internal Collaboration:

Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.

Stakeholder Engagement and Collaboration:

Collaborate closely with business and PM stakeholders in roadmap planning and implementation efforts and ensure technical milestones align with business requirements.

Security and Compliance:
Implement security measures and compliance standards to protect sensitive data and ensure adherence to industry regulations.

Mentorship:

Recruit, develop and mentor technical AI/ML engineering talent on the team Provide guidance and mentorship to junior MLOps engineers, fostering their professional growth and development.

Documentation:
Maintain comprehensive documentation of MLOps processes and procedures for reference and knowledge sharing.

Standards and Best Practices:
Ensure the use of standards, governance and best practices in ML pipeline monitoring and ML model monitoring, and adherence to model and data governance standards

Problem Solving:
Troubleshoot complex issues related to machine learning model deployments and data pipelines, and develop innovative solutions.

What We're Looking For:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Experienced professional (7+ years experience) as ML engineer, architect, engineer, lead data scientist in Big Data ecosystem or any similar distributed or public cloud platform, with a desire to assume greater responsibilities as a leader and mentor, while still being hands-on

4+ years hands-on experience in integrating, evaluating, deploying, operationalizing ML and LLM models at speed and scale, including integration with enterprise applications and APIs.

(In addition, ideal candidate should also have hands on experience on training and fine-tuning ML and LLM models at scale)
Expertise (4+ years) in distributed computing and orchestration technology (Kubernetes, Ray, Airflow) and scaling, as well as public cloud platform & systems (AWS, GCP, Azure)
Proficiency with Databricks, MLflow, Flink, GPT4All, , or similar AI/ML/ML Ops technologies
Experience developing with SQL, NoSQL, ElasticSearch, MongoDB, and Spark, Python, PySpark for model development and ML Ops
Excellent written & verbal communication and stakeholder management skill
Strategic thinker and influencer with demonstrated technical and business acumen and problem-solving skills
Experienced with LLMs (extractive and generative), fine-tuning and operationalizing LLM pipelines. Strong familiarity with higher level trends in LLMs and open-source platforms
This role is limited to persons with indefinite right to work in the United States.

Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is 150,000 – 230,000.

Final base salary for this role will be based on the individual's geographical location as well as experience and qualifications for the role.

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here )

.

About Company Statement:
S&P Global delivers essential intelligence that powers decision making.

We provide the world's leading organizations with the right data, connected technologies and expertise they need to move ahead.

As part of our team, you'll help solve complex challenges that equip businesses, governments and individuals with the knowledge to adapt to a changing economic landscape.

S&P Global Ratings

offers critical insights for credit, risk and sustainable finance solutions that are essential to translating complexity into clarity, so market participants can uncover opportunities.

_S&P Global has a Securities Disclosure and Trading Policy ("the Policy") that seeks to mitigate conflicts of interest by monitoring and placing restrictions on personal securities holding and trading.

The Policy is designed to promote compliance with global regulations. In some Divisions, pursuant to the Policy's requirements, candidates at S&P Global may be asked to disclose securities holdings.

Some roles may include a trading prohibition and remediation of positions when there is an effective or potential conflict of interest.

Employment at S&P Global is contingent upon compliance with the Policy._

S&P Global is an equal opportunity employer committed to making all employment decisions without regard to race/ethnicity, gender, pregnancy, gender identity or expression, color, creed, religion, national origin, age, disability, marital status (including domestic partnerships and civil unions), sexual orientation, military veteran status, unemployment status, or any other basis prohibited by federal, state or local law.

Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to:

and your request will be forwarded to the appropriate person.
The EEO is the Law Poster describes discrimination protections under federal law.
Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law.

Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: and your request will be forwarded to the appropriate person.

US Candidates Only:
The EEO is the Law Poster describes discrimination protections under federal law.
IFTECH Middle Professional Tier II (EEO Job Group)

Job ID:

292695

Posted On:

Location:
New York, New York, United States

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