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Tecton Jobs (NOW HIRING)

Parafin

Senior Software Engineer, ML Platform

$125K - $165K/yr

Preferred : • Databricks experience (MLflow, Model Serving). • Experience with feature stores (e.g., Tecton, Feast) and streaming (Kafka/Kinesis). • Experience with fintech, risk, or ...

LanceDB Inc

Senior Solutions Engineer

San Francisco, CA · On-site

$180K - $250K/yr

Have worked with feature stores (e.g., Feast, Tecton) or have designed custom ML feature pipelines. * Have experience in observability and monitoring (Prometheus, Grafana, ELK/EFK). * Are familiar ...

Intuit

Senior Staff AI/MLE Scientist

Mountain View, CA · On-site

$210K - $284K/yr

Strong software engineering fundamentals: experience contributing to and maintaining shared ML libraries, feature stores, or feature engineering frameworks (e.g., featlib, feat-layer, Feast, Tecton ...

NerdWallet, Inc

Staff Data Scientist

San Francisco, CA · On-site

$130 - $180/hr

Knowledge of streaming data architectures (e.g., Kafka, Kinesis), orchestration tools (e.g., Airflow, DBT), and feature stores (e.g., Tecton, Feast) * Domain experience in fintech, marketplaces ...

Intuit

Senior Staff AI/MLE Scientist

Mountain View, CA · On-site

$210K - $284K/yr

Strong software engineering fundamentals: experience contributing to and maintaining shared ML libraries, feature stores, or feature engineering frameworks (e.g., featlib, feat-layer, Feast, Tecton ...

Intuit

Senior Staff AI/MLE Scientist

San Diego, CA · On-site

$210K - $284K/yr

Strong software engineering fundamentals: experience contributing to and maintaining shared ML libraries, feature stores, or feature engineering frameworks (e.g., featlib, feat-layer, Feast, Tecton ...

Intuit

Senior Staff AI/MLE Scientist

San Diego, CA · On-site

$210K - $284K/yr

Strong software engineering fundamentals: experience contributing to and maintaining shared ML libraries, feature stores, or feature engineering frameworks (e.g., featlib, feat-layer, Feast, Tecton ...

Intuit

Senior Staff AI/MLE Scientist

Mountain View, CA · On-site

$210K - $284K/yr

Strong software engineering fundamentals: experience contributing to and maintaining shared ML libraries, feature stores, or feature engineering frameworks (e.g., featlib, feat-layer, Feast, Tecton ...

Forward Financing LLC

Lead Data Scientist

$160K - $220K/yr

Tecton) * Bachelor's degree in Financial/Apfplied Math, Operations Research, Economics, and/or Statistics. Masters/PhD is a plus. Compensation: Annual Salary: $160,000 - $220,000 USD Annual Bonus:

Basis Research

Data Engineer, Platform

New York, NY · On-site

$125K - $150K/yr

Experience with feature stores (Tecton, Feast) or building feature platforms. * Background in ML research or research engineering providing understanding of data needs across experiment lifecycle.

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Experience with feature stores (SageMaker Feature Store, Feast, Tecton, or similar); designing feature pipelines for both batch and real-time serving * Experiment Tracking & Registry: MLflow, Weights ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Experience with feature stores (SageMaker Feature Store, Feast, Tecton, or similar); designing feature pipelines for both batch and real-time serving * Experiment Tracking & Registry: MLflow, Weights ...

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Showing results 21-40

All JobsTecton Jobs

Tecton information

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.

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 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.
More about Tecton jobs
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Tecton jobs near you
Infographic showing various Tecton job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 68% Physical, and 32% Remote job distribution.

Cloud Engineer with public sector experience

Software People, Inc.

Austin, TX • On-site

$55.25 - $73.75/hr

Contractor

Re-posted 4 days ago

Job description

Phone/Skype Hire.  Onsite from Day 1 / Hybrid.

Location: Austin, Texas  

Duration: 6+ months

Need 3-page resumes. Must have current LinkedIn profile. Please complete the enclosed documentation in its entirety and always get RTR physically signed.

Responsibilities

A Software Developer Specialist will focus on engineering-related software services, including model ingestion, automated quantity extraction, plan conformance checks, and CI/CD automation. Leveraging PEPS ensures compliance with procurement regulations while enabling rapid onboarding of specialized talent.

The Senior Software Developer Specialist will be responsible for advancing AI initiatives by extending existing proof-of-concept (POC) solutions into scalable, production-ready web applications that directly support transportation engineering workflows. This role will focus on transforming early-stage AI models and prototypes—such as those supporting plan review automation, roadway asset detection, and digital delivery—into fully integrated applications accessible through secure, user-friendly web interfaces across the enterprise.

Skills Needed

Years

Required/Preferred

Experience

8

Required

Cloud Platforms: Experience with AWS, Azure, GCP, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, OCI AI Services).

8

Required

DevOps: Ansible, CI/CD, Docker and Kubernetes experience.

8

Required

Databases: SQL (PostgreSQL, MySQL) and NoSQL/vector databases.

8

Required

Scripting: Proficient in both Bash and PowerShell for automation.

8

Required

CI/CD Experience: Azure DevOps, GitHub Actions, Jenkins, or similar automation pipelines.

3

Required

Python: 3-5+ years production experience, this is your primary language.

3

Required

NLP/LLMs: Experience with transformers (BERT, GPT, T5), RAG systems, fine-tuning, prompt engineering, or building LLM applications.

3

Required

Time Series: Forecasting models, anomaly detection, sequential data modeling, or real-time monitoring systems.

3

Required

Recommender Systems: Collaborative filtering, ranking models, personalization engines, or content recommendations.

3

Required

MLOps Tools: Production experience with MLflow, Weights & Biases, Kubeflow, Airflow, or similar platforms.

3

Required

Distributed Training: Large-scale model training, multi-GPU/multi-node setups, efficient data parallelism.

3

Required

Computer Vision: Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference.

3

Required

Feature stores (Feast, Tecton) or advanced feature engineering.

3

Required

Model optimization: quantization, pruning, knowledge distillation.

3

Required

LLM Models: Ollama, Huggingface, or other non-frontier models

2

Required

AI/ML Production: Built and deployed 2-3+ ML models serving real users, not just experiments.

1

Preferred

Experience with Geospatial Information Systems (GIS) and analyzing spatial data.

1

Preferred

Prior experience in the transportation, logistics, or smart city sectors.

1

Preferred

Background in Computer Vision (object detection, image segmentation) applied to infrastructure or vehicular data.

1

Preferred

Familiarity with public sector data compliance, security, and governance standards.

1

Preferred

Experience with the Unreal gaming engine and real world digital twinning

1

Preferred

Experience with Google Maps Cesium API

1

Preferred

Experience with Polygonflow Dash and its capabilities