Senior Machine Learning Engineer
Summary
Designs, builds, and deploys production-grade ML systems (LLMs, pipelines, and automation tools) for a mid-market professional services firm’s AI-driven internal workflows, collaborating with data scientists, engineers, and stakeholders.
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