Software Engineer (ML Platform) Job at Together AI (Amsterdam)

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

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 Principal Data Platform Software Engineer

We’re looking for a Sr Principal Data Platform Software Engineer (P70) to be a k...

Location

Salary:

239400.00 - 312550.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

15+ years in Data Engineering, Software Engineering, or related roles, with substantial exposure to big data ecosystems
Demonstrated experience building and operating data platforms or large‑scale data services in production
Proven track record of building services from the ground up (requirements → design → implementation → deployment → ongoing ownership)
Hands‑on experience with AWS, GCP (e.g., compute, storage, data, and streaming services) and cloud‑native architectures
Practical experience with big data technologies, such as Databricks, Apache Spark, AWS EMR, Apache Flink, or StarRocks
Strong programming skills in one or more of: Kotlin, Scala, Java, Python
Experience leading cross‑team technical initiatives and influencing senior stakeholders
Experience mentoring Staff/Principal engineers and lifting the technical bar for a team or org
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

Job Responsibility

Design, develop and own delivery of high quality big data and analytical platform solutions aiming to solve Atlassian’s needs to support millions of users with optimal cost, minimal latency and maximum reliability
Improve and operate large‑scale distributed data systems in the cloud (primarily AWS, with increasing integration with GCP and Kubernetes‑based microservices)
Drive the evolution of our high-performance analytical databases and its integrations with products, cloud infrastructures (AWS and GCP) and isolated cloud environments
Help define and uplift engineering and operational standards for petabyte scale data platforms, with sub‑second analytic queries and multi‑region availability (coding guidelines, code review practices, observability, incident response, SLIs/SLOs)
Partner across multiple product and platform teams (including Analytics, Marketplace/Ecosystem, Core Data Platform, ML Platform, Search, and Oasis/FedRAMP) to deliver company‑wide initiatives that depend on reliable, high‑quality data
Act as a technical mentor and multiplier, raising the bar on design quality, code quality, and operational excellence across the broader team
Design and implement self‑healing, resilient data platforms with strong observability, fault tolerance, and recovery characteristics
Own the long‑term architecture and technical direction of Atlassian’s product data platform with projects that are directly tied to Atlassian’s company-level OKRs
Be accountable for the reliability, cost efficiency, and strategic direction of Atlassian’s product analytical data platform
Partner with executives and influence senior leaders to align engineering efforts with Atlassian’s long-term business objectives

What we offer

health and wellbeing resources
paid volunteer days

Fulltime

Senior Platform Engineer, ML Data Systems

We’re looking for an ML Data Engineer to evolve our eval dataset tools to meet t...

Location

United States , Mountain View

Salary:

137871.00 - 172339.00 USD / Year

Khan Academy

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
5 years of Software Engineering experience with 3+ of those years working with large ML datasets, especially those in open-source repositories such as Hugging Face
Strong programming skills in Go, Python, SQL, and at least one data pipeline framework (e.g., Airflow, Dagster, Prefect)
Experience with data versioning tools (e.g., DVC, LakeFS) and cloud storage systems
Familiarity with machine learning workflows — from training data preparation to evaluation
Familiarity with the architecture and operation of large language models, and a nuanced understanding of their capabilities and limitations
Attention to detail and an obsession with data quality and reproducibility
Motivated by the Khan Academy mission “to provide a free world-class education for anyone, anywhere.”
Proven cross-cultural competency skills demonstrating self-awareness, awareness of other, and the ability to adopt inclusive perspectives, attitudes, and behaviors to drive inclusion and belonging throughout the organization.

Job Responsibility

Evolve and maintain pipelines for transforming raw trace data into ML-ready datasets
Clean, normalize, and enrich data while preserving semantic meaning and consistency
Prepare and format datasets for human labeling, and integrate results into ML datasets
Develop and maintain scalable ETL pipelines using Airflow, DBT, Go, and Python running on GCP
Implement automated tests and validation to detect data drift or labeling inconsistencies
Collaborate with AI engineers, platform developers, and product teams to define data strategies in support of continuously improving the quality of Khan’s AI-based tutoring
Contribute to shared tools and documentation for dataset management and AI evaluation
Inform our data governance strategies for proper data retention, PII controls/scrubbing, and isolation of particularly sensitive data such as offensive test imagery.

What we offer

Competitive salaries
Ample paid time off as needed
8 pre-scheduled Wellness Days in 2026 occurring on a Monday or a Friday for a 3-day weekend boost
Remote-first culture - that caters to your time zone, with open flexibility as needed, at times
Generous parental leave
An exceptional team that trusts you and gives you the freedom to do your best
The chance to put your talents towards a deeply meaningful mission and the opportunity to work on high-impact products that are already defining the future of education
Opportunities to connect through affinity, ally, and social groups
401(k) + 4% matching & comprehensive insurance, including medical, dental, vision, and life.

Fulltime

Senior ML Platform Engineer

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP e...

Location

United States , Boston

Salary:

150000.00 - 210000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field
or equivalent practical experience
5+ years of experience in software engineering with a focus on ML infrastructure, cloud platforms, or MLOps
Strong programming skills in Python, with experience in building distributed systems and REST/gRPC APIs
Deep knowledge of cloud-native services and infrastructure-as-code (e.g., AWS CDK, Terraform, CloudFormation)
Hands-on experience with model deployment platforms such as AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks
Proficiency in ML lifecycle tools (MLflow, Weights & Biases, BentoML) and containerization strategies (Docker, Kubernetes)
Understanding of data engineering and ingestion pipelines, with ability to interface with data lakes, feature stores, and streaming systems
Proven ability to work cross-functionally with Data Science, Data Platform, and Software Engineering teams, influencing decisions and driving alignment
Passion for AI and automation to solve real-world problems and improve operational workflows

Job Responsibility

Architect, build, own, and operate scalable ML infrastructure in cloud environments (e.g., AWS), optimizing for speed, observability, cost, and reproducibility
Create, support, and maintain core MLOps infrastructure (e.g., MLflow, feature store, experiment tracking, model registry), ensuring reliability, scalability, and long-term sustainability
Develop, evolve, and operate MLOps platforms and frameworks that standardize model deployment, versioning, drift detection, and lifecycle management at scale
Implement and continuously maintain end-to-end CI/CD pipelines for ML models using orchestration tools (e.g., Prefect, Airflow, Argo Workflows), ensuring robust testing, reproducibility, and traceability
Partner closely with Data Science, Sensor Intelligence, and Data Platform teams to operationalize and support model development, deployment, and monitoring workflows
Build, manage, and maintain both real-time and batch inference infrastructure, supporting diverse use cases from physiological analytics to personalized feedback loops for WHOOP members
Design, implement, and own automated observability tooling (e.g., for model latency, data drift, accuracy degradation), integrating metrics, logging, and alerting with existing platforms
Leverage AI-powered tools and automation to reduce operational overhead, enhance developer productivity, and accelerate model release cycles
Contribute to and maintain internal platform documentation, SDKs, and training materials, enabling self-service capabilities for model deployment and experimentation
Continuously evaluate and integrate emerging technologies and deployment strategies, influencing WHOOP’s roadmap for AI-driven platform efficiency, reliability, and scale

What we offer

equity
benefits

Fulltime

Sr. Staff ML Platform Engineer

Machine learning is the crucial enabler for every financial service that EarnIn ...

Location

United States , Mountain View

Salary:

360000.00 - 440000.00 USD / Year

EarnIn

Expiration Date

Until further notice

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field
8+ years of industry machine learning experience and excellent software engineering skills
Strong programming skills in Python, with familiarity in ML frameworks such as TensorFlow or PyTorch
Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI
Familiarity with data pipelines and workflow management tools
Strong communication and collaboration skills
Passion for learning and staying updated with the latest industry trends in machine learning and platform engineering

Job Responsibility

Design, build, and maintain a robust ML platform and tooling ecosystem that supports the entire machine learning lifecycle, from experimentation to production
Lead and mentor a team of ML engineers, deeply understanding their workflows to streamline model training, deployment, and monitoring, while ensuring reproducibility and consistency of results
Drive scalability, reliability, and cost efficiency of the ML platform, balancing performance with ease of use for scientists and engineers
Evaluate and adopt emerging technologies to continually advance the organization’s machine learning capabilities and maintain a competitive edge
Champion operational excellence, setting a high bar for engineering quality, reliability, and automation
Act as a catalyst for innovation, spearheading step-change improvements that unlock new opportunities for growth and efficiency

What we offer

equity and benefits

Fulltime

Site Reliability Engineer SRE – ML platform

Location

United States , Sunnyvale

Salary:

Not provided

Thirdeye Data

Expiration Date

Until further notice

Requirements

6+ years of experience in ML Ops with strong knowledge in Kubernetes, Python, MongoDB and AWS
Good understanding of Apache SOLR
Proficient with Linux administration
Knowledge of ML models and LLM
Ability to understand tools used by data scientists and experience with software development and test automation
Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS)
Experience working with cloud computing and database systems
Experience building custom integrations between cloud-based systems using APIs
Experience developing and maintaining ML systems built with open-source tools
Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes

Job Responsibility

Continuous Deployment using GitHub Actions, Flux, Kustomize
Design and implement cloud solutions, build MLOps on AWS cloud
Data science model containerization, deployment using Docker, VLLM, Kubernetes
Communicate with a team of data scientists, data engineers, and architects, and document the processes
Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
Knowledge of ML models and LLM

Fulltime

Senior Software Engineer, Data Products

As a Senior Software Engineer, you will play a pivotal role in the development o...

Location

United States , Los Angeles

Salary:

143000.00 - 180000.00 USD / Year

Fox Corporation

Expiration Date

Until further notice

Requirements

Experience working in Software Engineering, Data Science, ML Engineering
Strong background in live media streaming and handling VOD content
Expertise in working with live media streaming
Experience working with Vector Database
Strong understanding of generative AI technologies and their underlying mechanisms
Good grasp of distributed system design
Experience with TensorFlow, PyTorch etc.
REST or GraphQL API Design Experience
Proficient with building batch and streaming data pipelines on cloud platforms

Job Responsibility

Design and implement novel and scalable AI solutions for real business problems
Design and implement workflows to generate and manage assets for live streaming and VOD
Build workflow orchestrations that can be readily extended to perform new analyses
Prototype new approaches and productionize solutions at scale for hundreds of millions of active users
Maintain high-level craftsmanship while delivering meaningful results
Mentor junior engineers on the team
Collaborate with peers, engineering leadership, and product management

What we offer

Annual discretionary bonus
Medical/dental/vision insurance
401(k) plan
Paid time off

Fulltime

Software Engineer (ML Platform)

Together AI

Location:
Netherlands , Amsterdam

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 18, 2026

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