Senior Software Engineer

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

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 Software Engineer II - AI/ML

As a Senior Software Engineer II at Aledade, we maintain, improve, and expand ou...

Location

United States

Salary:

Not provided

Aledade, Inc.

Expiration Date

Until further notice

Requirements

BS/BTech (or higher) in Computer Science, Engineering or a related field
6+ years experience as an engineer building full-stack web applications as part of a cross-functional team
3+ years of experience working with SQL or other database querying language on large multi-table data sets
3+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value
3+ years of experience coaching other engineers

Job Responsibility

Develop and implement scalable and performant solutions
Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes
Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work
Improve AI/ML infrastructure for model development, training, and deployment, with a focus on large language models and other generative AI architectures
Design multi-year vision, shaping the direction of crucial generative AI areas - text generation, image synthesis, multimodal models, and personalized content creation
Architect systems to enhance the capabilities and relevance of AI models, making complex data sets more accessible and actionable
Design and implement prompt engineering strategies to effectively guide generative AI models
Work closely with Product Management, Practices, Sales, Customer Success, and other stakeholders to identify and prioritize applied AI use cases within the organization
Analyze product usage patterns and trends to make data-driven decisions and forecasts for generative AI applications
Maintain the security of protected patient health information and ensure compliance with relevant regulations in the context of AI

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

We're looking for a Software Engineer to join our Data Department, someone with ...

Location

Spain , Madrid

Salary:

Not provided

Fever

Expiration Date

Until further notice

Requirements

Strong backend engineering foundations and a passion for writing high-quality Python code
Solid understanding of OOP, software architecture patterns (clean architecture, hexagonal), and design principles
Experience working with relational databases and SQL (PostgreSQL, Snowflake, or similar)
Familiarity with containerization and deployment workflows (Docker, Kubernetes)
Comfortable communicating in English in a cross-functional technical environment
Pragmatic mindset — you balance technical quality with business impact and speed of delivery

Job Responsibility

Build and maintain backend services and data pipelines that enable ML models and automations to run reliably at scale
Design robust systems to automate business processes and make them available through APIs or event-based architectures
Translate complex business and analytical needs into technical solutions that create leverage across CRM, Marketing, Product, and Data Science teams
Own your services end-to-end, from architecture to deployment and monitoring, applying strong engineering discipline
Collaborate closely with Data Science, Machine Learning and Data Engineering to ensure smooth integration of data sources and model infrastructure

What we offer

Responsibility from day one and professional and personal growth
Opportunity to have a real impact in a high-growth global category leader
A compensation package consisting of base salary and the potential to earn a significant bonus for top performance
Stock options plan
40% discount on all Fever events and experiences
Health insurance and other benefits such as Flexible remuneration with a 100% tax exemption through Cobee
English / Spanish Lessons
Wellhub Membership
Possibility to receive in advance part of your salary by Payflow

Fulltime

Senior Full Stack Software Engineer

Tutor Intelligence builds software to enable ordinary robots to achieve extraord...

Location

United States , Watertown

Salary:

140000.00 - 190000.00 USD / Year

Tutor Intelligence

Expiration Date

Until further notice

Requirements

Strong programming skills in Python
Software engineering tooling: git, unix shell, etc
Collaborative nature and social skill set
Interest in robotics, AI, solving hard problems, or improving the future of humanity
Passion for building things (and just getting stuff done)

Job Responsibility

Architecting and engineering core software across one or more of: robot software, backend services, ML services, cloud infrastructure / dev-ops
Involvement in new project planning

What we offer

generous equity
fully covered health + dental
unlimited PTO

Fulltime

Senior Machine Learning Infrastructure Engineer

As a Senior ML Infrastructure Engineer at Plus, you will design scalable archite...

Location

United States , Santa Clara

Salary:

160000.00 - 200000.00 USD / Year

PlusAI

Expiration Date

Until further notice

Requirements

Phd or MS in Computer Science, Electrical Engineering, or related field
Good oral and written communication skills
Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems
Proficiency in in Python, C++, SQL
Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on-prem environments)
Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect)
Strong knowledge of distributed systems, databases, and storage solutions
Extensive software design and development skills
Ability to learn and adapt to new technologies and contribute in a productive environment

Job Responsibility

Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale
Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks
Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability
Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure
Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems
Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform
Mentor junior engineers and contribute to a culture of technical excellence
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
Ensure team compliance with QMS, monitor quality, and drive process improvements

What we offer

Work, learn and grow in a highly future-oriented, innovative and dynamic field
Wide range of opportunities for personal and professional development
Catered free lunch, unlimited snacks and beverages
Highly competitive salary and benefits package, including 401(k) plan

Fulltime

Senior Software Engineer - ML Infrastructure

SimpliSafe

Location:
United States , Boston

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 19, 2026

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