Senior
Machine Learning Engineer<\/span><\/b>
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Location:
Hybrid – Arlington, Virginia<\/span>
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Employment
Type: Full -time<\/span>
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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.<\/span>
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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.<\/span>
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What
will you do<\/span><\/b>
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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.<\/span>
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Responsibilities:<\/b>
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• <\/span><\/span><\/span>Design,
develop, and deploy scalable machine learning models and pipelines into
production environments.
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• <\/span><\/span><\/span>Translate
business problems into well -scoped ML solutions in close collaboration with
data scientists, engineers, and business stakeholders.
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• <\/span><\/span><\/span>Build
and maintain end -to -end ML pipelines from data ingestion and feature
engineering through model serving and monitoring.
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• <\/span><\/span><\/span>Lead
model evaluation, A/B testing, and ongoing performance monitoring across
deployed systems.
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• <\/span><\/span><\/span>Partner
with MLOps and platform engineering teams to ensure reliable, reproducible, and
cost -effective model deployment.
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• <\/span><\/span><\/span>Drive
technical decisions on ML frameworks, model architectures, and tooling
standards across the AI practice.
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• <\/span><\/span><\/span>Mentor
and develop junior ML engineers, establishing team -wide engineering standards
and code quality practices.
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• <\/span><\/span><\/span>Document
model design decisions, experiment results, and deployment configurations to
support organizational learning.
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Requirements:<\/b>
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US
Citizen or Permanent Resident authorized to work in the United States.<\/span>
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Experience:
7–10 years of experience in machine learning engineering or applied ML, with a
strong emphasis on production systems.<\/span>
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ML
Frameworks: Expert -level proficiency in PyTorch, TensorFlow, or equivalent
frameworks, with a proven record of shipping models to production.<\/span>
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Engineering:
Advanced Python skills; comfort with distributed systems, containerization
(Docker/Kubernetes), and cloud -based ML infrastructure (AWS, GCP, or Azure).<\/span>
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Data:
Solid command of feature engineering, data versioning, and large -scale data
processing (Spark, Ray, or similar).<\/span>
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Collaboration:
Strong ability to work across technical and non -technical stakeholders, clearly
communicating model behavior, tradeoffs, and limitations.<\/span>
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Preferred:<\/b>
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Hands -on
experience with large language models (LLMs), fine -tuning, retrieval -augmented
generation (RAG), or prompt engineering pipelines.<\/span>
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Familiarity
with MLOps platforms such as MLflow, Weights & Biases, or Kubeflow.<\/span>
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Experience
building AI -powered internal tools, copilots, or automation workflows.<\/span>
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Background
in enterprise or professional services environments.<\/span>
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Advanced
degree (MS or PhD) in Machine Learning, Computer Science, Statistics, or a
related field.<\/span>
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Benefits:<\/b>
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• <\/span><\/span><\/span>Family
Health Care (54% cost covered for the entire family)
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• <\/span><\/span><\/span>Family
Dental (54% cost covered for the entire family)
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• <\/span><\/span><\/span>Family
Vision (54% cost covered for the entire family)
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• <\/span><\/span><\/span>Flexible
Spending Account
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• <\/span><\/span><\/span>Performance
bonuses tied to project and delivery milestones
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• <\/span><\/span><\/span>Lifetime
Event Bonuses (e.g., new child, marriage)
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• <\/span><\/span><\/span>Profit -sharing
arrangement for any work brought into the company
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• <\/span><\/span><\/span>Unlimited
Leave with Approval
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• <\/span><\/span><\/span>401k
– 100% employer match on first 4% invested
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• <\/span><\/span><\/span>$1,500
annual training and conference budget
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Job
Type: Full -time, Permanent Position<\/span>
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Work Authorization:<\/b>
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US
Citizen or Permanent Resident; no active security clearance required.<\/span>
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Schedule:<\/b>
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Monday
to Friday<\/span>
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Work Location:<\/b>
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Hybrid
– Arlington, Virginia<\/span>
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