Senior Machine Learning Engineer

Senior Machine Learning Engineer

Location: Hybrid – Arlington, Virginia

Employment Type: Full-time

BizFirst is assisting our client with the hiring of a Senior Machine Learning Engineer to help design, build, and deploy production-grade machine learning systems that will fundamentally reshape how the organization operates internally. This is a high-impact role at the center of the client’s AI transformation effort, working across data pipelines, model development, and production deployment in a collaborative, fast-moving environment.

Our client is a mid-market professional services organization that is actively rethinking how it designs and executes its core business operations through artificial intelligence and automation. The company is building a dedicated AI capability to embed machine learning and generative AI into its most critical internal workflows – from decision support and process automation to real-time analytics and intelligent document processing.

What will you do

The ideal candidate will have significant experience (7–10 years) in machine learning engineering, with a strong background in building and shipping models at scale in production environments. Experience working on large-scale data systems and collaborating closely with data scientists, product teams, and platform engineers is essential. Hands-on experience with large language models (LLMs) and generative AI frameworks is strongly preferred.

Responsibilities:

•       Design, develop, and deploy scalable machine learning models and pipelines into production environments.

•       Translate business problems into well-scoped ML solutions in close collaboration with data scientists, engineers, and business stakeholders.

•       Build and maintain end-to-end ML pipelines from data ingestion and feature engineering through model serving and monitoring.

•       Lead model evaluation, A/B testing, and ongoing performance monitoring across deployed systems.

•       Partner with MLOps and platform engineering teams to ensure reliable, reproducible, and cost-effective model deployment.

•       Drive technical decisions on ML frameworks, model architectures, and tooling standards across the AI practice.

•       Mentor and develop junior ML engineers, establishing team-wide engineering standards and code quality practices.

•       Document model design decisions, experiment results, and deployment configurations to support organizational learning.

Requirements:

US Citizen or Permanent Resident authorized to work in the United States.

Experience: 7–10 years of experience in machine learning engineering or applied ML, with a strong emphasis on production systems.

ML Frameworks: Expert-level proficiency in PyTorch, TensorFlow, or equivalent frameworks, with a proven record of shipping models to production.

Engineering: Advanced Python skills; comfort with distributed systems, containerization (Docker/Kubernetes), and cloud-based ML infrastructure (AWS, GCP, or Azure).

Data: Solid command of feature engineering, data versioning, and large-scale data processing (Spark, Ray, or similar).

Collaboration: Strong ability to work across technical and non-technical stakeholders, clearly communicating model behavior, tradeoffs, and limitations.

Preferred:

Hands-on experience with large language models (LLMs), fine-tuning, retrieval-augmented generation (RAG), or prompt engineering pipelines.

Familiarity with MLOps platforms such as MLflow, Weights & Biases, or Kubeflow.

Experience building AI-powered internal tools, copilots, or automation workflows.

Background in enterprise or professional services environments.

Advanced degree (MS or PhD) in Machine Learning, Computer Science, Statistics, or a related field.

Benefits:

•       Family Health Care (54% cost covered for the entire family)

•       Family Dental (54% cost covered for the entire family)

•       Family Vision (54% cost covered for the entire family)

•       Flexible Spending Account

•       Performance bonuses tied to project and delivery milestones

•       Lifetime Event Bonuses (e.g., new child, marriage)

•       Profit-sharing arrangement for any work brought into the company

•       Unlimited Leave with Approval

•       401k – 100% employer match on first 4% invested

•       $1,500 annual training and conference budget

Job Type: Full-time, Permanent Position

Work Authorization:

US Citizen or Permanent Resident; no active security clearance required.

Schedule:

Monday to Friday

Work Location:

Hybrid – Arlington, Virginia