ML Infra Engineer (Data Systems) Job at Physical Intelligence (San Francisco)

Data Engineer

Influur is redefining how advertising works, through creators, data, and AI. Our...

Location

Mexico , Mexico City

Salary:

Not provided

Influur

Expiration Date

Until further notice

Requirements

Strong programming with Python and SQL
Comfortable building from scratch and improving existing code
Expertise in data modeling and warehousing, including dimensional modeling and performance tuning
Experience designing and operating ETL and ELT pipelines with tools like Airflow or Dagster, plus dbt for transformations
Hands-on with batch and streaming systems and with Lakehouse or warehouse tech on AWS or GCP
Proficiency integrating third-party APIs and datasets, ensuring reliability, lineage, and governance
Familiarity with AI data needs: feature stores, embedding pipelines, vector databases, and feedback loops that close the gap between model and outcome
High standards for code quality, testing, observability, and CI
Comfortable with Docker and modern cloud infra

Job Responsibility

Treats data as a product and ships improvements that users feel
Moves fast without breaking trust
Owns problems across the stack, from ingestion to modeling to serving
Communicates clearly with ML engineers, analysts, and business partners
Experiments, measures, and iterates
Sees ambiguity as a chance to design the standard everyone else will follow

What we offer

Competitive equity in a venture-backed company
Opportunities to grow and develop
Remote work

Fulltime

Data Engineer

Influur is redefining how advertising works, through creators, data, and AI. Our...

Location

Colombia , Bogotá

Salary:

Not provided

Influur

Expiration Date

Until further notice

Requirements

Strong programming with Python and SQL
Comfortable building from scratch and improving existing code
Expertise in data modeling and warehousing, including dimensional modeling and performance tuning
Experience designing and operating ETL and ELT pipelines with tools like Airflow or Dagster, plus dbt for transformations
Hands-on with batch and streaming systems and with Lakehouse or warehouse tech on AWS or GCP
Proficiency integrating third-party APIs and datasets, ensuring reliability, lineage, and governance
Familiarity with AI data needs: feature stores, embedding pipelines, vector databases, and feedback loops that close the gap between model and outcome
High standards for code quality, testing, observability, and CI
Comfortable with Docker and modern cloud infra

Job Responsibility

Treats data as a product and ships improvements that users feel
Moves fast without breaking trust. You value contracts, schemas, and backward compatibility
Owns problems across the stack, from ingestion to modeling to serving
Communicates clearly with ML engineers, analysts, and business partners
Experiments, measures, and iterates. You set measurable SLAs and keep them green
Sees ambiguity as a chance to design the standard everyone else will follow

What we offer

Competitive equity in a venture-backed company
Opportunities to grow and develop
Remote work

Fulltime

Data Engineer

Influur is redefining how advertising works, through creators, data, and AI. Our...

Location

Argentina , Buenos Aires

Salary:

Not provided

Influur

Expiration Date

Until further notice

Requirements

Strong programming with Python and SQL
Comfortable building from scratch and improving existing code
Expertise in data modeling and warehousing, including dimensional modeling and performance tuning
Experience designing and operating ETL and ELT pipelines with tools like Airflow or Dagster, plus dbt for transformations
Hands-on with batch and streaming systems and with Lakehouse or warehouse tech on AWS or GCP
Proficiency integrating third-party APIs and datasets, ensuring reliability, lineage, and governance
Familiarity with AI data needs: feature stores, embedding pipelines, vector databases, and feedback loops that close the gap between model and outcome
High standards for code quality, testing, observability, and CI
Comfortable with Docker and modern cloud infra

Job Responsibility

Treats data as a product and ships improvements that users feel
Moves fast without breaking trust. You value contracts, schemas, and backward compatibility
Owns problems across the stack, from ingestion to modeling to serving
Communicates clearly with ML engineers, analysts, and business partners
Experiments, measures, and iterates. You set measurable SLAs and keep them green
Sees ambiguity as a chance to design the standard everyone else will follow

What we offer

Competitive equity in a venture-backed company
Opportunities to grow and develop
Remote work

Fulltime

Principal Engineer - Marketplace

Principal Engineer role in the Marketplace Engineering team to lead breakthrough...

Location

United States , San Francisco; Sunnyvale

Salary:

302000.00 - 336000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master’s degree with 12+ years of industry experience
10+ years of experience building and deploying ML models in large-scale production environments
Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch, JAX) and distributed computing platforms (Spark, Ray)
Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, Algorithmic Game Theory, and Large-scale Ads Ranking/Auction Systems
Proven track record of leading complex ML projects from research through production with significant measurable business impact
Strong programming skills in Python, Java, or Go with experience building production ML systems
Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives
Advanced Deep Learning and Neural Network architectures
Scalable ML architecture and distributed model training

Job Responsibility

Lead the design and implementation of advanced ML systems for dynamic pricing algorithms serving millions of drivers across 70+ countries around the world
Architect real-time ML infrastructure handling 1M+ pricing decisions per second with sub-50ms latency requirements
Drive breakthrough research in causal ML, reinforcement learning, algorithmic game theory, and multi-objective optimization for marketplace optimization with strategic agents
Own end-to-end ML model lifecycle from research through production deployment and continuous optimization
Develop and enforce best practices in system design, ensuring data integrity, security, and optimal performance
Serve as a representative for the Marketplace organization to the broader internal and external technical community
Contribute to the eng brand for Marketplace and serve as a talent magnet to help attract and retain talent for the team
Stay abreast of industry trends and emerging technologies in software engineering, focused particularly on ML/AI, to enhance our systems and processes continually
Build scalable ML architecture and feature management systems supporting Driver Pricing and broader Marketplace teams
Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligible to participate in a 401(k) plan
Eligible for various benefits (details at provided link)

Fulltime

Staff Data Engineer

At Vanta, our mission is to help businesses earn and prove trust. We believe tha...

Location

United States

Salary:

213000.00 - 251000.00 USD / Year

Vanta

Expiration Date

Until further notice

Requirements

Have at least six years of experience working with data
Have at least two years of experience in Software Engineering or a related field
Have experience with common analytics tooling (e.g. Stitch/Fivetran, Snowflake/BigQuery/Redshift, dbt, Airflow, Dagster, Looker/Mode/Sigma)
Have led an implementation of Debezium or another CDC event tracking system
Have good working knowledge of AWS data infra systems and Terraform
Bring a system-oriented and software engineering mindset to the Data Engineering practice
Deep knowledge of crafting dimensional and fact models in modern data fashion
Have a passion for enabling the developer experience of data
Desire to lead the industry in security, anonymization, and compliance management when it comes to data warehousing
Open to using AI to amplify their skills and strengthen their work

Job Responsibility

Design and implement complex data models, modeling metadata, building reports and dashboards and creating reporting tools for data science and ML products users
Design and deploy data infrastructure needed to drive data-driven decision-making solutions
Be the company’s expert on data administration and master data management
Be a technical thought leader on the development of scalable data systems
Develop front end applications to expose analytical data sets enterprise wide
Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses
Work with the Product and Enterprise Engineering system teams to structure source systems for reporting consumption across the enterprise
Help maintain the CDC pipeline to power customer reporting

What we offer

Offers Equity
Medical benefits
401(k) plan
Other company perk programs
Comprehensive medical, dental, and vision coverage, with 100% of employee-only benefit premiums covered for most medical plans
16 weeks fully-paid Parental Leave for all new parents
Health & wellness stipend
Remote workspace, internet, and cellphone stipend
Commuter benefits for team members who report to the SF and NYC office
Family planning benefits

Fulltime

Data Platform Engineer

Our enterprise clients are moving from fragmented data foundations to AI-first d...

Location

Switzerland , Genève

Salary:

Not provided

Randstad

Expiration Date

April 30, 2026

Requirements

Strong background in data engineering for large-scale systems
Proven experience delivering production-grade data pipelines
Familiarity with enterprise data landscapes and constraints
Engineering-first approach to data
Strong ownership and accountability for data reliability
Comfortable operating in complex, multi-stakeholder environments
High standards for robustness, scalability, and maintainability

Job Responsibility

Design, build, and maintain scalable batch and streaming data pipelines
Implement data ingestion from heterogeneous enterprise sources (databases, APIs, events, files)
Structure data for downstream AI and ML consumption
Ensure data quality, consistency, and availability across environments
Build and operate feature stores and analytical data layers for ML
Design data models optimized for training and inference workloads
Enable efficient data access patterns for real-time and near-real-time AI use cases
Support experimentation while enforcing production-grade standards
Translate business and AI requirements into robust data architectures
Collaborate closely with AI/ML Engineers, MLOps, Infra, Security, and Product teams

Fulltime

Machine Learning Data Engineer - Systems & Retrieval

As a Machine Learning Data Engineer - Systems & Retrieval, you will build and op...

Location

United States , Palo Alto

Salary:

Not provided

Zyphra

Expiration Date

Until further notice

Requirements

Strong software engineering background with fluency in Python
Experience designing, building, and maintaining data pipelines in production environments
Deep understanding of data structures, storage formats, and distributed data systems
Familiarity with indexing and retrieval techniques for large-scale document corpora
Understanding of database systems (SQL and NoSQL), their internals, and performance characteristics
Strong attention to security, access controls, and compliance best practices (e.g., GDPR, SOC2)
Excellent debugging, observability, and logging practices to support reliability at scale
Strong communication skills and experience collaborating across ML, infra, and product teams

Job Responsibility

Design and implementation of distributed data ingestion and transformation pipelines
Building retrieval and indexing systems that support RAG and other LLM-based methods
Mining and organizing large unstructured datasets, both in research and production environments
Collaborating with ML engineers, systems engineers, and DevOps to scale pipelines and observability
Ensuring compliance and access control in data handling, with security and auditability in mind

What we offer

Comprehensive medical, dental, vision, and FSA plans
Competitive compensation and 401(k)
Relocation and immigration support on a case-by-case basis
On-site meals prepared by a dedicated culinary team
Thursday Happy Hours

Fulltime

Senior CVML Platform Engineer

We are seeking a Senior CVML Platform Engineer to help design, build, and evolve...

Location

United States

Salary:

160000.00 - 287000.00 USD / Year

Blue River Technology

Expiration Date

Until further notice

Requirements

5+ years of professional engineering experience, with a focus on platform, infrastructure, or systems engineering
Strong technical judgment, balancing the evolution of legacy platforms with the design and delivery of new, greenfield components shared across multiple teams and workloads
Excellent Python skills, used in production systems, tooling, and platform components
Solid understanding of ML systems and the end-to-end model development lifecycle, from experimentation to deployment and iteration
Hands-on experience or strong familiarity with cloud platforms (AWS preferred) and container orchestration systems such as Kubernetes and Slurm
Ability to partner effectively with ML engineers, infra teams, and product stakeholders to translate requirements into platform capabilities
Ability to quickly ramp up on new domains, tools, and complex existing systems

Job Responsibility

Design, build, and evolve platform capabilities that support ML training, batch inference, and model deployment workflows at scale
Own and improve core platform components (e.g., compute orchestration, data pipelines, inference systems) used by multiple teams across Blue River and John Deere
Continuously enhance platform reliability, scalability, and performance, with a focus on real-world ML workloads
Enable ML engineers to move faster by building intuitive, well-documented platform tools and workflows across the model lifecycle (experimentation, deployment, and iteration)
Improve model inference performance and throughput while balancing trade-offs among cost, latency, and reliability
Support and scale distributed training and inference systems, including frameworks such as Ray and related tooling
Develop and optimize hybrid compute environments (cloud + on-prem/GPU infrastructure) to support large-scale ML workloads
Build and maintain infrastructure leveraging Kubernetes, Slurm, and cloud platforms (AWS preferred)
Identify and resolve bottlenecks in compute, storage, and data movement pipelines
Evaluate existing platform systems and make thoughtful decisions on when to extend, refactor, or rebuild components

What we offer

bonus and benefit programs

Fulltime

ML Infra Engineer (Data Systems)

Physical Intelligence

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 21, 2026

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