Artificial Intelligence & Machine Learning Engineer, Vice President - AI Labs

Blackrock

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Atlanta, GA
Salary
$170,000–$220,000 / yr
Posted
32 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $212k
This role $195k
$160k most similar roles pay here $265k

This role pays less than 65% of similar roles. Most pay $177,900–$246,150 — the shaded band above. At the midpoint, this role pays about $195k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Blackrock

BlackRock is the world''s largest asset management firm, providing investment management, risk management, and advisory services to institutional and retail clients through its Aladdin technology platform. Industry: Asset Management & Financial Services

Blackrock currently has 81 open roles on FindRole.

Listed pay typically runs $147,500–$195,000 across 77 roles with salary data.

Most-posted roles

View all roles at Blackrock

At a glance

TL;DR · Artificial Intelligence & Machine Learning Engineer, Vice President - AI Labs

Role Posting Log in to save

Artificial Intelligence & Machine Learning Engineer, Vice President - AI Labs joins the AI Labs team to provide technical leadership and architectural direction for advanced science and engineering initiatives. The role involves designing, building, and operating production AI/ML systems, including generative AI, intelligent agents, predictive modeling, and optimization engines. You will develop reusable platforms, infrastructure, and data pipelines while establishing engineering standards and mentoring others. Key responsibilities include optimizing workloads for latency, throughput, and cost while ensuring security in regulated environments. Required skills include proficiency in Python and SQL, experience with Docker, Kubernetes, and distributed systems. The role utilizes technologies such as PyTorch, TensorFlow, JAX, and various cloud ML platforms to solve complex challenges in financial services, specifically focusing on investment insights, risk management solutions, and enterprise AI platforms that automate and scale operations.

Skills

Python SQL Docker Kubernetes PyTorch TensorFlow JAX scikit-learn MLOps Generative AI Distributed Systems Data Pipelines API Design Rust C++ Go R Java AWS SageMaker Azure ML Vertex AI

What you'll do

  • Provide technical leadership and set architectural direction for multidisciplinary teams.
  • Design, build, and operate production AI/ML systems including generative AI and intelligent agents.
  • Develop reusable AI platforms, services, and infrastructure to accelerate firm-wide adoption.
  • Translate emerging AI capabilities into scalable solutions that deliver measurable business impact.
  • Define evaluation, testing, and observability approaches for non-deterministic and agentic applications.
  • Optimize AI workloads for latency, throughput, compute efficiency, reliability, security, and cost.
  • Partner with cross-functional teams to move solutions from concept through production deployment.
  • Establish engineering standards and mentor engineers while influencing technical strategy across the firm.

What we're looking for

  • Must have 12+ years of software engineering experience building and operating complex production systems.
  • Must have 6+ years of experience building and deploying AI/ML, optimization, or model-driven applications in production.
  • Must possess strong proficiency in Python to develop maintainable and well-tested production software.
  • Must have strong SQL skills and experience with data-intensive applications and large-scale datasets.
  • Must have experience designing and building APIs, services, data pipelines, or distributed systems for AI/ML applications.
  • Must have experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Must demonstrate the ability to lead technical solutions from architecture and design through production deployment and operation.
  • Must possess strong problem-solving, collaboration, and communication skills to influence decisions across multidisciplinary teams.

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