Staff Machine Learning Engineer

Indeed; Richmond (VA); On-site; USD 199,000 - 299,000; Full time

Benefits offered by this job

401k

RSUs

Open PTO

11 holidays per year

Parental leave (26 wks)

Job summary

Indeed is seeking a Staff Machine Learning Engineer to lead the Employer Agents Team. You will own a major workstream, collaborate with cross‑functional partners, and drive ML/AI projects including Agentic solutions and LLM‑based systems.

You’ll shape technical direction and guide team members toward product and technical goals. You will explore data, formulate problems, build agentic experiences, and enhance LLMOps reliability and infrastructure, mentoring other engineers and delivering

Qualifications

• Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field with extensive experience; or advanced degrees with reduced years.
• Proven familiarity with agent orchestration frameworks and LLM observability tools.
• Demonstrated success deploying ML solutions to large production systems across teams.
• Strong foundation in data structures and algorithms.

Responsibilities

• Partner with cross‑functional teams to optimize search algorithms for accuracy and user experience.
• Experiment with ML model improvements, scale to production, and run A/B tests for matching tech.
• Define priorities, deliverables, and success criteria with stakeholders.
• Bridge between technical and non‑technical teams, communicating goals clearly.
• Mentor and grow software engineers and ML engineers across teams.
• Break down large ML initiatives into incremental, value-delivering pieces.
• Represent Indeed at major ML conferences (NeurIPS, ICML, ICLR).

Skills

Agent orchestration

LLM observability

Prompt optimization

Production ML deployment

Data structures & algorithms

Deep learning frameworks

English communication

Education

Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field

Master’s degree

PhD

Tools

Torch

TensorFlow

LLM tooling

Data pipelines

Job description

Day to Day

As a Staff Machine Learning Engineer, you will be a team lead on the Employer Agents Team. Your team will be responsible for driving value and better customer experiences for our employer‑facing Agentic solutions, helping redefine the employer hiring journey through AI. You will own one of the team's major workstreams, partner with cross‑functional teams to develop and deliver ML and AI projects, including Agentic solutions, LLMs‑as‑a‑Judge, evaluation capabilities, and ML systems and models, and help drive technical direction for the team while guiding other members to achieve product and technical goals. On a daily basis, you will explore data, formulate problem statements, build new agentic experiences, and drive improvements in our LLMOps reliability and infrastructure.

Responsibilities

• Partner with cross‑functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
• Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
• Define and clarify project priorities, deliverables, and success criteria in partnership with cross‑functional teams.
• Act as a bridge between technical and non‑technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
• Mentor and grow other software engineers and Machine Learning Engineers across teams
• Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
• Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).

Skills/Competencies

• Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with 3 years experience
• Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
• Prior success in deploying impactful Machine Learning solutions to large‑scale production systems, while partnering across teams
• Solid knowledge of data structures and algorithms
• Sense of ownership and accountability as a key contributor in the technical and product domains
• Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
• Excellent written and verbal communication in English, effective with technical and business audiences

Salary Range Transparency

Tier 1 - United States of America 163,000 - 245,000 USD per year

Tier 2 - United States of America 182,000 - 272,000 USD per year

Tier 3 - United States of America 199,000 - 299,000 USD per year

Tier 4 - United States of America N/A

Tier 5 - United States of America 227,000 - 341,000 USD per year

Salary Range Disclaimer

The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job‑related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region‑specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site (https://www.indeed.com/careers/paytiers), and recruiters can confirm how location is considered for a specific role.

Benefits - Health, Work/Life Harmony, & Wellbeing

We care about what you care about. We have a multitude of benefits to support Indeedians, as well as their pets, kids, and partners including medical, dental, vision, disability and life insurance. Indeedians are able to enroll in our company’s 401k plan, as well as an equity‑based incentive program. Indeedians will also receive open paid time off, 11 paid holidays a year and up to 26 weeks of paid parental leave. For more information, select your country and learn more about our employee benefits, program, & perks at https://www.indeed.com/careers/benefits!

Equal Opportunities and Accommodations Statement

Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We’re proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro‑diversity, disability, age, or veteran status, or any other non‑merit based or legally protected grounds.

Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit https://www.indeed.com/careers/accommodations. If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview.

Inclusion & Belonging

Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we’re committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. We believe that fostering an inclusive environment where every employee feels respected and accepted benefits everyone, fueling innovation and creativity.

We value diverse experiences, including those who have had prior contact with the criminal legal system. We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment.

Those with military experience are encouraged to apply. Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome.