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Machine Learning Engineer

HappyRobotSan FranciscoEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Posted
10 Aug 2026
Status
Open · checked 7d ago

About this role

Role Overview

The Machine Learning Engineer role at HappyRobot involves building conversational AI models that enable human-like interactions within an innovative infrastructure setting. Based in San Francisco with remote flexibility, this position suits an autonomous engineer passionate about taking cutting-edge research and transforming it into scalable real-time systems.

Key Responsibilities

Design, build, and maintain scalable machine learning systems covering data ingestion, preprocessing, training, testing, and deployment.
Develop and optimize end-to-end machine learning pipelines to guarantee high reliability and reproducibility.
Implement robust MLOps methodologies, incorporating model versioning, experiment tracking, CI/CD procedures, and continuous production monitoring.
Partner closely with product and engineering groups to integrate models into real-time products efficiently.
Maintain high standards for data quality, observability, and overall performance across all enterprise AI solutions.

Requirements

Extensive background in deep learning, machine learning, and natural language processing.
Proven expertise in MLOps and production data pipelines like model deployment, monitoring, and scaling.
Working knowledge of Python alongside familiarity with Go.
Hands-on experience utilizing ML lifecycle management utilities such as MLflow, Kubeflow, and Weights & Biases.
Exceptional coding, debugging, and data engineering capabilities.
Entrepreneurial mindset emphasizing ownership, independence, and deep immersion in problem-solving.

Nice to Have

Background in speech recognition, text-to-speech, or audio processing technologies.
Acquaintance with generative AI, large language models, and real-time inference frameworks.
Practical knowledge regarding data orchestration platforms including Airflow, Prefect, and Dagster.
Prior involvement in fast-paced startup atmospheres.
Understanding of cloud services like AWS, GCP, or Azure alongside containerization tools such as Docker and Kubernetes.

Skills and Tools

Python and Go programming
Machine Learning Operations (MLOps)
Natural Language Processing (NLP)
ML lifecycle platforms (MLflow, Kubeflow, Weights & Biases)
Data orchestration utilities like Airflow
Cloud infrastructure (AWS, GCP, Azure)
Containerization (Docker, Kubernetes)

Salary and Benefits

Competitive salary paired with equity opportunities in a fast-growing startup environment.
Comprehensive healthcare packages including medical, dental, and vision coverage.

About the Company

HappyRobot provides foundational infrastructure allowing global enterprises to build and manage autonomous AI workforces across voice, email, and internal systems. Originating from Y Combinator's S23 batch and backed by prominent investors such as a16z and Base10, the organization has raised over $60 million to power critical operational workflows for enterprises worldwide.

How to Apply

Interested candidates should visit the official HappyRobot careers page to submit their application and CV for review.

Skills and tech stack

PythonAWSGCPAzureKubernetesDockerNLPMLOpsAirflow

Questions candidates ask

Is this position remote?

Yes, this role offers remote work options alongside a San Francisco location.

What programming languages are required?

Proficiency in Python is required, along with familiarity in Go.

What benefits are included?

The position includes competitive salary, equity, and comprehensive healthcare, dental, and vision coverage.

What background does HappyRobot look for in ML tools?

Candidates should have experience with ML lifecycle management tools like MLflow, Kubeflow, and Weights & Biases.

How can I apply for this job?

You can apply by visiting the official HappyRobot company careers page.

Ready to apply?

The application is on the official HappyRobot careers page.

Apply on company site