ML Infrastructure Engineer Job at AppLovin (Palo Alto)

Senior Software Engineer - ML Infrastructure

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems
Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks)
Proven experience delivering reliable and scalable infrastructure in production
Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability
Strong communication skills and ability to collaborate across teams

Job Responsibility

Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems
Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development
Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency
Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration
Contribute to technical strategy and architecture discussions within the team
Mentor and support other engineers through code reviews, design discussions, and technical guidance

What we offer

medical, dental, vision, and 401(k)

Fulltime

Data Infrastructure Engineer

A venture-backed startup at the intersection of AI and national security is buil...

Location

United States , New York City Metropolitan Area

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

Strong engineering experience in Python, Go, or C
Experience building and scaling production data systems
Hands-on expertise with model deployment and ML Ops practices
Knowledge of database design, performance tuning, and operations
Someone who thrives in early-stage, fast-paced environments and enjoys tackling complex challenges

Job Responsibility

Build and maintain the data pipelines and infrastructure that power ML applications
Deploy and manage models at scale, from training through production
Design APIs and services that integrate smoothly into mission-critical workflows
Ensure data is handled and secured properly across large, distributed environments
Collaborate closely with a small, fast-moving team to solve hard technical problems in real-world settings

What we offer

Significant equity
Strong health & wellness benefits

Fulltime

Engineering Manager - Machine Learning Infrastructure

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

241200.00 - 400000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

8–10 years of experience in ML infrastructure, including direct hands-on expertise as an engineer, IC/TL
2+ years of experience managing infrastructure or ML platform engineers
Proven experience delivering and operating ML or AI infrastructure at scale
Solid technical depth across ML/AI infrastructure domains (e.g., feature stores, pipelines, deployment, inference, observability)
Demonstrated ability to drive execution on complex technical projects with cross-team stakeholders
Strong communication and stakeholder management skills

Job Responsibility

Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments
Build and launch Plaid’s next-generation feature store to improve reliability and velocity of model development
Define and drive adoption of an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines, deployment tooling, and inference systems
Partner with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration
Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

Data Infrastructure Engineer

This young, early-stage start-up challenger are currently looking for a hands-on...

Location

United States , New York or DC

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

Startup Energy: You thrive in fast-paced environments, manage ambiguity well, and focus on what moves the needle
Designing and deploying intuitive, user-friendly APIs
Demonstrated ability to train and deploy models at scale
Successfully launching machine learning services, particularly those leveraging LLMs, embeddings, and inference, into production environments
Handling and securing large-scale production data
Demonstrated proficiency in Python, Go, or C
A proactive approach to tackling complex challenges in a fast-paced, early-stage environment
A passion for innovation and a collaborative spirit

Job Responsibility

Developing secure data sharing middleware
Integrating software seamlessly into the workflows of specialized professionals, ensuring secure and efficient data access throughout the asset recruitment process
Building, shipping and supporting mission critical services in support of the services that make up the Data platform
Providing solutions for the full data stack – from the data management, software development and model and deployment lifecycles

What we offer

Competitive Salary + Equity

Fulltime

Data Infrastructure Engineer

This young, early-stage start-up challenger is currently looking for a hands-on ...

Location

United States , New York or DC

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

Startup Energy: You thrive in fast-paced environments, manage ambiguity well, and focus on what moves the needle
Designing and deploying intuitive, user-friendly APIs
Demonstrated ability to train and deploy models at scale
Successfully launching machine learning services, particularly those leveraging LLMs, embeddings, and inference, into production environments
Handling and securing large-scale production data
Demonstrated proficiency in Python, Go, or C
A proactive approach to tackling complex challenges in a fast-paced, early-stage environment
A passion for innovation and a collaborative spirit

Job Responsibility

Developing secure data sharing middleware
Integrating software seamlessly into the workflows of specialised professionals, ensuring secure and efficient data access throughout the asset recruitment process
Providing solutions for the full data stack – from the data management, software development and model and deployment lifecycles

What we offer

Equity
Opportunity to work with an Ambitious, Rapidly-Growing Start-Up

Fulltime

Engineering Manager, Infrastructure

As an Engineering Manager for the Infrastructure team, you’ll lead the engineers...

Location

Canada; United States

Salary:

195000.00 - 285000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

5+ years of hands-on software or infrastructure engineering experience
2+ years of experience leading teams of senior and staff-level engineers in platform, SRE, or infrastructure domains
Proven ability to design and operate large-scale distributed systems in cloud environments (preferably GCP or AWS)
Expertise with Kubernetes, Docker, Terraform, Ubuntu, and CI/CD pipelines
Familiarity with observability tools (Grafana, Prometheus, ELK, Datadog, NewRelic) and performance tuning
Strong grounding in networking, security, and reliability principles
Experience managing infrastructure costs, availability SLAs, and high-throughput systems at scale

Job Responsibility

Lead, coach, and grow a distributed team of high-impact Infrastructure Engineers
Partner with senior engineering leadership on strategic initiatives such as cloud migration, infrastructure scaling, platform reliability, and cost efficiency
Define and implement modern operational excellence practices, including SLOs, error budgets, incident reviews, and performance monitoring
Guide technical decision-making across key areas like Kubernetes, GCP, observability, networking, CI/CD, and IaC (Terraform, Ansible)
Collaborate with AI, Data, and Product Engineering teams to ensure infrastructure scalability for ML and AI-native workloads
Run effective 1:1s, career development conversations, and quarterly performance reviews
Support recruiting efforts to attract top engineering talent across time zones

What we offer

Equity
Company bonus or sales commissions/bonuses
401(k) plan
At least 10 paid holidays per year
Flex PTO
Parental leave
Employee assistance program and wellbeing benefits
Global travel coverage
Life/AD&D/STD/LTD insurance
FSA/HSA and medical, dental, and vision benefits

Fulltime

Software Engineer, Data Infrastructure

The Data Infrastructure team at Figma builds and operates the foundational platf...

Location

United States , San Francisco; New York

Salary:

149000.00 - 350000.00 USD / Year

Figma

Expiration Date

Until further notice

Requirements

5+ years of Software Engineering experience, specifically in backend or infrastructure engineering
Experience designing and building distributed data infrastructure at scale
Strong expertise in batch and streaming data processing technologies such as Spark, Flink, Kafka, or Airflow/Dagster
A proven track record of impact-driven problem-solving in a fast-paced environment
A strong sense of engineering excellence, with a focus on high-quality, reliable, and performant systems
Excellent technical communication skills, with experience working across both technical and non-technical counterparts
Experience mentoring and supporting engineers, fostering a culture of learning and technical excellence

Job Responsibility

Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence
Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company
Manage data ingestion, movement, and processing through core platforms like Snowflake, our ML Datalake, and real-time streaming systems
Improve data reliability, consistency, and performance, ensuring high-quality data for engineering, research, and business stakeholders
Collaborate with AI researchers, data scientists, product engineers, and business teams to understand data needs and build scalable solutions
Drive technical decisions and best practices for data ingestion, orchestration, processing, and storage

What we offer

equity
health, dental & vision
retirement with company contribution
parental leave & reproductive or family planning support
mental health & wellness benefits
generous PTO
company recharge days
a learning & development stipend
a work from home stipend
cell phone reimbursement

Fulltime

Senior Software Engineer - Network Enablement (Applied ML)

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong software engineering skills including systems design, APIs, and building reliable backend services (Go or Python preferred)
Production experience with batch and streaming data pipelines and orchestration tools such as Airflow or Spark
Experience building or operating real-time scoring and online feature-serving systems, including feature stores and low-latency model inference
Experience integrating model outputs into product flows (APIs, feature flags) and measuring impact through experiments and product metrics
Experience with model lifecycle and operations: model registries, CI/CD for models, reproducible training, offline & online parity, monitoring and incident response

Job Responsibility

Embed model inference into Network Enablement product flows and decision logic (APIs, feature flags, backend flows)
Define and instrument product + ML success metrics (fraud reduction, retention lift, false positives, downstream impact)
Design and run experiments and rollout plans (backtesting, shadow scoring, A/B tests, feature-flagged releases) to validate product hypotheses
Build and operate offline training pipelines and production batch scoring for bank intelligence products
Ship and maintain online feature serving and low-latency model inference endpoints for real-time partner/bank scoring
Implement model CI/CD, model/version registry, and safe rollout/rollback strategies
Monitor model/data health: drift/regression detection, model-quality dashboards, alerts, and SLOs targeted to partner product needs
Ensure offline and online parity, data lineage, and automated validation / data contracts to reduce regressions
Optimize inference performance and cost for real-time scoring (batching, caching, runtime selection)
Ensure fairness, explainability and PII-aware handling for partner-facing ML features

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

ML Infrastructure Engineer

AppLovin

Location:
United States , Palo Alto

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
March 08, 2026

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Job Posted:March 08, 2026

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