Jobs

Staff Machine Learning Engineer, Public Sector
San Francisco, CA; St. Louis, MO; New York, NY; Washington, DC
·
On-site
·
Full-time
·
1w ago
Compensation
$260,400 - $362,250
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Commuter Benefits
•Healthcare
•401k
•Equity
•Learning
•Commuter
Required Skills
Python
PyTorch
Machine Learning
ML Systems Engineering
Retrieval Systems
Embeddings
The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale.
Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge, we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators.
You will:
-
Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability.
-
Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data.
-
Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently.
-
Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets.
-
Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions.
-
Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts.
-
Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments.
-
Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams.
-
Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization.
This role will require an active security clearance or the ability to obtain a security clearance.
Ideally You’d Have:
-
8+ years of experience building and deploying applied ML systems in production environments.
-
Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps.
-
Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation.
-
Hands-on experience with retrieval systems, embeddings, or representation learning.
-
Proficiency in Python and modern ML frameworks (ex: Py Torch), with the ability to design systems end to end.
-
Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production.
-
Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity.
Nice to Haves:
-
High ownership over 0→1 systems that move directly into production.
-
Real-world constraints that force thoughtful engineering tradeoffs, not just model tuning.
-
Opportunity to shape foundational agentic infrastructure used across multiple teams and missions.
-
Work that blends research depth with applied impact, in environments where correctness, robustness, and trust matter.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
The base salary range for this full-time position in the location of Washington DC is:$260,400—$326,600 USD
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$289,800—$362,250 USDPlease reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado is:$260,400—$326,600 USD
**PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
*We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. *
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
*We comply with the United States Department of Labor's Pay Transparency provision. *
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Total Views
0
Apply Clicks
0
Mock Applicants
0
Scraps
0
Similar Jobs

Spacecraft Qualification Engineer
Planet Labs · San Francisco, CA

Product Manufacturing Engineer
OpenAI · San Francisco

Software Engineer, Embedded Security Focus
Planet Labs · San Francisco, CA

Engineering Manager, Security Engineering
Brex · San Francisco, California, United States

Software Engineer, Event Response
Waymo · San Francisco, CA, USA
About Scale AI

Scale AI
Series CAccelerate the development of AI applications.
501-1,000
Employees
San Francisco
Headquarters
$7.3B
Valuation
Reviews
3.5
2 reviews
Work Life Balance
1.5
Compensation
3.5
Culture
2.0
Career
3.0
Management
1.5
25%
Recommend to a Friend
Pros
Famous in tech world
Good for career transitions
Offers equity after 1 year
Cons
Extremely long working hours (80+ per week)
Unprofessional recruiting process
Poor communication during hiring
Salary Ranges
0 data points
Junior/L3
L3
Junior/L3 · Data Scientist L3
0 reports
$123,049
total / year
Base
-
Stock
-
Bonus
-
$104,592
$141,506
Interview Experience
5 interviews
Difficulty
3.2
/ 5
Duration
14-28 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 60%
Negative 20%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Final Round
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
News & Buzz
CCC Intelligent Solutions Appoints Chief Product Officer to Scale AI-Driven Innovation Across the Industry - Business Wire
Source: Business Wire
News
·
5w ago
Industry insight: photonics to scale AI data centers - Nature
Source: Nature
News
·
5w ago
Building trust to scale AI: Interview with the CEO of Stack Overflow - McKinsey & Company
Source: McKinsey & Company
News
·
5w ago
Decagon AI raises $250M at $4.5B valuation to scale AI concierge platform - SiliconANGLE
Source: SiliconANGLE
News
·
5w ago