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Tecton Jobs in California (NOW HIRING)

ML Platform Engineer

Los Angeles, CA · On-site

$170 - $300/hr

Experience implementing feature stores (Feast, Tecton, or internal systems). * Production work with Ray Serve, KServe, Triton, BentoML, SageMaker, Vertex AI, or custom gRPC inference services.

Showing results 21-23

Tecton information

See California salary details

$8

$25

$60

How much do tecton jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for tecton in California is $25.79, according to ZipRecruiter salary data. Most workers in this role earn between $14.83 and $30.13 per hour, depending on experience, location, and employer.

What is a Tecton?

Tecton engineers are professionals who specialize in building and managing feature platforms for machine learning applications. They work with data pipelines, infrastructure, and tools to ensure high-quality, real-time, and batch feature data is accessible for ML models. Tecton engineers often collaborate with data scientists and ML engineers to streamline the process of developing, deploying, and monitoring machine learning features, enabling faster and more reliable AI solutions.

What skills and qualifications are needed to work as a Machine Learning Platform Engineer at Tecton?

To excel as a Machine Learning Platform Engineer at Tecton, you need a solid background in computer science, data engineering, and machine learning, often demonstrated by a relevant degree and prior experience building data infrastructure. Familiarity with tools like Python, SQL, cloud platforms (AWS, GCP, Azure), and technologies such as Apache Spark or Kubernetes is typically required. Strong problem-solving abilities, collaboration, and effective communication help you work with cross-functional teams and address complex engineering challenges. These skills are vital for designing scalable systems that enable efficient development and deployment of machine learning models.

What are the most common challenges faced by Machine Learning Engineers working with Tecton in deploying real-time features?

Machine Learning Engineers using Tecton often encounter challenges related to integrating real-time feature pipelines with existing data infrastructure and ensuring low-latency performance. Managing data quality, monitoring feature freshness, and coordinating deployments across teams can be complex, especially as models scale to production. Close collaboration with data engineers and DevOps teams is essential for maintaining robust, automated data pipelines and troubleshooting issues quickly.

What is the difference between Tecton vs Data Engineer?

AspectTectonData Engineer
Primary RoleBuilds and manages feature stores for machine learning modelsDesigns, develops, and maintains data pipelines and infrastructure
Skills & CertificationsMachine learning, data engineering, cloud platforms, SQLData pipeline tools, SQL, Python, cloud services
Work EnvironmentCollaborates with data scientists and ML teamsWorks with data engineers, analysts, and software teams
Industry UsageUsed in organizations deploying ML modelsUsed across data-driven companies for data infrastructure

While both Tecton and Data Engineers work with data infrastructure, Tecton specializes in building feature stores for machine learning applications, whereas Data Engineers focus on creating data pipelines and managing data infrastructure for various business needs. The roles often overlap but serve different core functions within data teams.

Infographic showing various Tecton job openings in California as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 62% Physical, and 38% Remote job distribution, with an average salary of $53,653 per year, or $25.8 per hour.

ML Platform Engineer

Hadrian Automation

Los Angeles, CA • On-site

$170 - $300/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Job description

Hadrian - Manufacturing the Future

Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.


Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.


Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen.


If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.

The Role

This is an ML infrastructure role at the core of Hadrian’s technology stack. While Data Science, Operations Research, Vision, and Document AI teams build models, you will own the platform that ensures these models remain reliable, effective, and secure in production. You’ll standardize our deployment patterns built around MLflow, Dagster, ECR, FastAPI, and EKS, making them the backbone for packaging, evaluating, releasing, serving, monitoring, and rolling back models across Hadrian’s automated factories.

What You’ll Do
  • Build the production platform that enables Hadrian’s factories to safely depend on models for drawing extraction, cycle-time prediction, forecasting, scheduling, and more—with measurable performance and fast rollback.

  • Develop shared batch and online serving for tabular, vision, document-AI, scheduling, graph, and embedding workloads, targeting clear SLAs for latency, availability, and isolation.

  • Create repeatable release and evaluation processes featuring automated tests, reproducible artifacts, lineage, shadow deployments, canaries, and A/B tests.

  • Own online feature serving and maintain contract integrity with offline feature tables; proactively detect and address training-serving skew, feature drift, bad data, and model degradation.

  • Build operational tooling for telemetry, incident response, autoscaling, resource and GPU management, cost attribution, and secure model routing.

  • Develop APIs, SDKs, reusable templates, and documentation that teams can adopt without requiring close support from platform engineers.

What We’re Looking For
  • Track record building and operating production ML infrastructure across multiple models or inference workloads.

  • Strong production-level Python and SQL skills, including typing, testing, packaging, API design, and building observability features.

  • Hands-on experience with Kubernetes, containers, and handling distributed-system failure modes such as retries, partial failures, idempotence, and resource isolation.

  • Engineering background with model registries, feature systems, batch/real-time inference, experiment tracking, or model CI/CD workflows.

  • Practical judgment around latency, throughput, availability, multi-tenancy, autoscaling, and infrastructure cost optimizations.

  • Ability to build stable interfaces and collaborate closely with engineering and scientific stakeholders.

What Will Set You Apart
  • Experience implementing feature stores (Feast, Tecton, or internal systems).

  • Production work with Ray Serve, KServe, Triton, BentoML, SageMaker, Vertex AI, or custom gRPC inference services.

  • Experience serving and evaluating vision, document-understanding, embedding, or generative pipelines.

  • Expertise in GPU inference optimization, multi-model serving, edge inference, or Go/Rust performance-sensitive AI services.

  • Background in regulated environments or open-source contributions to ML infrastructure projects (MLflow, Feast, KServe, Ray).

Compensation

Salary range: $170,000 – $300,000

This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will depend on several factors, including relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business needs.

Benefits
  • Medical, dental, vision, and life insurance

  • 401(k)

  • Flexible vacation policy

ITAR Requirements

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U.S. citizen, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

Equal Opportunity Employer

Hadrian provides equal employment opportunity to all applicants and employees. We do not unlawfully discriminate based on race, color, religion, sex, gender identity, gender expression, national origin, ancestry, citizenship, age, disability, medical condition, veteran status, marital status, sexual orientation, genetic information, or any other protected characteristic. Reasonable accommodations are available for qualified individuals with disabilities.

Benefits for Full-time Employees
  • Medical, dental, vision, and life insurance plans for employees

  • 401k

  • Relocation support may be provided for certain situations, based on business need.

  • Flexible vacation policy

  • Equity

ITAR Requirements

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.

Use of AI in hiring

Hadrian uses AI-assisted tools in our recruiting and hiring processes to help our team work more efficiently. This may include tools that help organize and analyze recruiting data, as well as an AI-powered notetaker that can record and transcribe interviews and help coordinate feedback. These tools support our team and are not used to make hiring decisions. All candidate evaluations and hiring decisions are performed by humans. If an interview will be recorded, you will be notified in advance and may opt out at any time with no impact on your candidacy. Candidate data processed through these tools is subject to the same protections described in our Privacy Policy.

Hadrian Is An Equal Opportunity Employer

It is the Company’s policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions.

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