ML Engineer, Training Infrastructure Job at Prior Labs (Berlin)

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

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

Senior ML Data Engineer

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream,...

Location

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred
At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities
Strong foundation in computer science principes and statistical methods
Strong experience with cloud technology (AWS or Azure)
Strong experience with creation of data ingestion pipeline and ET process
Strong knowledge of big data tool such as Spark, Databricks and Python
Strong understanding of common machine learning techniques and frameworks (e.g. mlflow)
Strong knowledge of Natural language processing (NPL) concepts
Strong knowledge of scrum practices and agile mindset

Job Responsibility

Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads
Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance
Build and maintain feature stores, vector/embedding stores, and core data assets for ML
Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring
Implement data quality checks, drift detection, and automated retraining processes
Optimise cost, latency, and performance across all AI/ML infrastructure
Collaborate with data scientists and engineers to deliver production-ready ML and AI systems
Ensure AI/ML systems meet governance, security, and compliance requirements
Mentor teams and drive innovation across both agentic and classical ML engineering practices
Participate in team meetings and contribute to project planning and strategy discussions

What we offer

Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days
Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately
Pension: Awin offers access to an additional pension insurance to all employees in Germany
Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development
Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Senior Software Engineer - Data Infrastructure

We build the data and machine learning infrastructure to enable Plaid engineers ...

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

5+ years of software engineering experience
Extensive hands-on software engineering experience, with a strong track record of delivering successful projects within the Data Infrastructure or Platform domain at similar or larger companies
Deep understanding of one of: ML Infrastructure systems, including Feature Stores, Training Infrastructure, Serving Infrastructure, and Model Monitoring OR Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration
Strong cross-functional collaboration, communication, and project management skills, with proven ability to coordinate effectively
Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions
Demonstrated leadership abilities, including experience mentoring and guiding junior engineers

Job Responsibility

Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid
Leading key data infrastructure projects such as improving ML development golden paths, implementing offline streaming solutions for data freshness, building net new ETL pipeline infrastructure, and evolving data warehouse or data lakehouse capabilities
Working with stakeholders in other teams and functions to define technical roadmaps for key backend systems and abstractions across Plaid
Debugging, troubleshooting, and reducing operational burden for our Data Platform
Growing the team via mentorship and leadership, reviewing technical documents and code changes

What we offer

medical, dental, vision, and 401(k)
equity and/or commission

Fulltime

ML Engineer, Training Infrastructure

Prior Labs

Location:
Germany; United States , Berlin ▼
Freiburg
New York
San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 21, 2026

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