Lead Machine Learning Engineering, (Hybrid)

Cisco
Seattle, San Jose
Workplace: HybridFull timeUSD 197,500 - 249,800 annuallyFunction: Data Science & Machine LearningExperience: 8+ yearsEducation: bachelorsSkills: ["Communication","Mentorship","Influencing stakeholders","Engineering excellence","Problem-solving"]

Build and improve the data and ML systems that power LLMs and AI models, with a hands-on focus on creating high-quality training and evaluation datasets at scale. Design scalable data pipelines, advance human-in-the-loop labeling workflows, and develop synthetic data strategies. Apply ML and LLM techniques to automate data generation, scoring, and evaluation, while measuring dataset failure modes and linking dataset changes to model performance.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Cisco
Cisco
3 days ago

Lead Machine Learning Engineering, (Hybrid)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Build and improve the data and ML systems that power LLMs and AI models, with a hands-on focus on creating high-quality training and evaluation datasets at scale. Design scalable data pipelines, advance human-in-the-loop labeling workflows, and develop synthetic data strategies. Apply ML and LLM techniques to automate data generation, scoring, and evaluation, while measuring dataset failure modes and linking dataset changes to model performance.
Location: Seattle, San Jose
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and maintain robust, scalable data pipelines across the full ML/LLM lifecycle from ingestion to production-ready deployment.
  • •Architect and manage human-in-the-loop labeling workflows, including task generation, quality control, and feedback integration.
  • •Develop scalable synthetic data generation, filtering, and validation strategies to improve dataset diversity, coverage, and quality.
  • •Use LLMs and advanced ML techniques to automate data generation, labeling, scoring, and evaluation.
  • •Measure and mitigate dataset failure modes such as bias, contamination, and distribution shifts, linking dataset composition changes to model performance.

Pay and Benefits

Salary: USD 197,500 - 249,800 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401kPaid ParentalLong-term DisabilityBasic LifePaid HolidaysPaid Leave

Key Requirements

  • •Bachelor’s degree in a STEM field with 8+ years of relevant experience, or Master’s with 6+ years, or PhD with 3+ years of industry/academic research experience.
  • •3+ years of hands-on experience building, curating, and scaling datasets for machine learning training and evaluation.
  • •5+ years of professional programming experience using Python, C++, or Go in a production or research environment.
  • •5+ years of experience using machine learning frameworks such as PyTorch, TensorFlow, or equivalent to develop, train, evaluate, and deploy models.
  • •Experience with the full LLM lifecycle dataset needs, including synthetic data generation and post-training workflows such as SFT and RLHF (preferred).
Experience:8+ yearsMachine learningLLMsData engineeringSynthetic dataHuman-in-the-loop
Education:Bachelor's in STEM
Skills:CommunicationMentorshipInfluencing stakeholdersEngineering excellenceProblem-solving
Tech Stack:PythonC++GoPyTorchTensorFlowLLMsAgentsSparkRayBeamSFTRLHF

Company Brief

Cisco
Global technology company that designs, manufactures, and sells networking hardware, telecommunications equipment, and high-technology services and products for enterprises, service providers, and governments worldwide.
Industry: Networking Equipment
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1984
Glassdoor
Glassdoor: 4.0
WebsiteLinkedInGlassdoor