Senior Machine Learning Engineer (Active TS/SCI Clearance)

Striveworks
Fort Belvoir, VA
Hybrid

Who this role is best for

Candidates with experience in agentic AI systems and real-world AI deployment will find this mission-critical role with a hybrid work arrangement in the government domain.

Best fit for

  • Candidates with experience in agentic AI systems and real-world AI deployment
    — “delivering the most trusted AI systems operating in real-world use cases
  • Individuals with a strong background in Python and machine learning frameworks
    — “excellence in Python is essential, as is knowledge of TensorFlow, PyTorch, and/or scikit-learn
  • Candidates who have led or managed cross-functional engineering teams
    — “Experience leading, managing, or mentoring small, cross-functional engineering teams

Things to consider

  • Must have active TS/SCI clearance and be a US citizen for eligibility
    — “Active TS/SCI security clearance and US citizenship
  • Hybrid work with up to 15% travel to customer locations
    — “You will be hybrid/on site at customer locations at Fort Belvoir in Fairfax County, VA. You will be expected to travel up to 15% of the time.

How to stand out

  • Highlight experience with monitoring AI performance and managing data drift in production systems
    — “providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift
  • Emphasize your ability to define and deliver complex technical solutions for government clients
    — “Experience defining, scoping, planning, and delivering complex, production-level technical solutions
  • Showcase your work with unstructured data types like image, video, and text
    — “develop machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Industry

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed machine learning models
  • Orchestrated data engineering pipelines
  • Defined requirements for AI systems
  • Deployed models in real-world use cases
Typical background
Machine LearningData EngineeringDevOps

Skills & requirements

Required

Machine LearningData EngineeringModel DevelopmentAgentic SystemsAI OperationsMonitoring PerformanceManaging DriftSustaining SystemsImage, Video, Text, Geospatial, Time Series, Structured DataPythonTensorFlowPyTorchscikit-learnSoftware EngineeringDevOps

Preferred

Advanced Degree In Data ScienceClient-server SystemsContainerized/cloud EnvironmentsUnstructured DataComplex Technical SolutionsTeam LeadershipSecure Government Environments

Stack & domain

PythonTensorFlowPyTorchscikit-learnData StructuresDesign PatternsSystems Programming LanguageContainerized EnvironmentsCloud EnvironmentsUnstructured Data TypesComplex Technical SolutionsCross-functional Engineering TeamsAIMachine LearningData ScienceComputer Science

About the role

Original posting from Striveworks via Greenhouse

“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks 

The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.

Striveworks was built to solve that problem.

What you’ll build

Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.

As a Senior Machine Learning Engineer, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you’ll define requirements and orchestrate complex data engineering pipelines. You’ll also develop machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data. Your work will inform the future of Chariot, our proprietary AI operations platform. The work extends to the field, with mission-critical deployments, direct customer contact, and insights that shape what we build next.

What it’s like here

We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.

What we’re looking for

A BS degree in computer science, machine learning, or a related discipline and 6+ years of relevant experience

Experience integrating LLMs and/or building AI agents, agentic workflows, or agentic systems

Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of TensorFlow, PyTorch, and/or scikit-learn

Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language

Proficiency with modern software engineering tools and processes

Active TS/SCI security clearance and US citizenship

The following isn’t required, but we’d love to see it:

An advanced degree in data science, machine learning, computer science, or a related discipline

Knowledge of relevant architectures and design patterns for client-server systems

Experience implementing and deploying software into containerized or cloud environments

Experience with a variety of unstructured data types

Experience defining, scoping, planning, and delivering complex, production-level technical solutions

Experience leading, managing, or mentoring small, cross-functional engineering teams 

Experience delivering novel technology solutions in secure government environments

You will be hybrid/on site at customer locations at Fort Belvoir in Fairfax County, VA. You will be expected to travel up to 15% of the time.

Compensation

The anticipated base pay range for this position is $185,000–$230,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

Benefits include:

Medical/dental/vision insurance

Voluntary life, long-term disability, accident, and hospital indemnity insurance

HSA and FSA (including dependent care FSA) plans

401(k) plan

Unlimited PTO

Paid parental leave

Ready to build systems that work for a mission that matters? Let’s talk.

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact People Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

Source: Striveworks careers (Greenhouse)

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