Machine Learning Data Engineer - Systems & Retrieval Job at Zyphra (Palo Alto)

Senior Machine Learning Systems Engineer

Our organization drives AI innovation across Jira products. We deliver seamless ...

Location

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Extensive experience building Machine Learning and AI solutions (4+ years)
Proven experience developing, deploying, and maintaining end-to-end ML systems, including data engineering, model serving, and monitoring
Expert proficiency with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems
Expert proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX
Experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models

Job Responsibility

Collaborate with software engineers, data scientists, and product managers to solve complex problems
Lead projects from technical design through launch
Partner with teams to achieve impactful results
Deliver robust ML solutions to build AI features reaching millions
This includes curating ML datasets, fine-tuning open-source LLMs, or accessing proprietary LLMs
Mentor junior members of the team

What we offer

Health and wellbeing resources
Paid volunteer days

Senior Machine Learning Engineer

We’re seeking a Senior Machine Learning Engineer (P50) to join our new GenAI Mod...

Location

Singapore

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Extensive experience (generally 5+ years) in ML systems engineering, backend engineering, or infrastructure roles
Strong background in one or more of: LLMs, NLP, search/retrieval, embeddings, or applied ML
Hands-on experience with at least one GenAI area: RAG pipelines, fine-tuning, hybrid retrieval, or orchestration frameworks
Proficiency with modern ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex)
Familiarity with vector databases (Weaviate, Pinecone, FAISS, etc.) and large-scale serving infra
Strong coding skills (Python, backend engineering) and ability to move fast from idea to prototype
Comfort working in fast-paced, experimental environments with evolving direction
Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent experience

Job Responsibility

Build and apply advanced GenAI models
Develop and fine-tune LLMs and embeddings for Atlassian’s unique knowledge and enterprise data
Implement retrieval-augmented generation (RAG), hybrid retrieval, and knowledge-grounded modeling approaches
Work hands-on with modern frameworks, contributing directly to high-value prototypes and experiments
Prototype and experiment quickly
Build proof-of-concept systems for GenAI-powered assistants, agentic workflows, and innovative user experiences
Run experiments, collect feedback, and iterate fast to validate impact
Design and implement evaluation methods for quality, groundedness, and user value
Collaborate and contribute
Work closely with peers across ML, engineering, and product teams to bring new ideas to life

What we offer

Health and wellbeing resources
Paid volunteer days

Machine Learning Engineer - Data Foundation and AI

You’ll be a machine learning engineer on the Data Foundation & AI team. In this ...

Location

United States , New York

Salary:

186000.00 - 236400.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

1-3 years of experience training, deploying, and scaling ML/AI models in production environments
Strong experience with distributed systems and ML operations — from large-scale training to low-latency serving and monitoring
Proficiency in Python and modern ML frameworks (e.g., PyTorch), with the ability to implement and optimize complex models
Hands-on experience building or scaling ML/AI infrastructure, pipelines, or reusable platforms that support multiple teams
Curiosity and drive to experiment with advanced AI techniques (e.g., embeddings, retrieval, generative modeling) while staying grounded in production impact
Ability to thrive in a collaborative environment, working with both technical and non-technical partners to drive measurable outcomes

Job Responsibility

Building and scaling advanced ML/AI systems that power core Plaid products and applications used by millions of consumers
Driving impact at scale by improving distributed training, serving, and ML operations to make Plaid’s AI capabilities faster, more reliable, and more widely available
Developing new AI applications that enable innovative product experiences across fintech
Tackling 0 to 1 problems where you explore new approaches, as well as scaling 1 to 10 systems for reliability and efficiency
Collaborating with some of the strongest MLEs at Plaid in a high-ownership, bottom-up driven team
Experimenting with cutting-edge ML and AI techniques while balancing practical productionization and measurable business impact

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

Machine Learning Engineer - Data Foundation and AI

You’ll be a machine learning engineer on the Data Foundation & AI team. In this ...

Location

United States , San Francisco

Salary:

186000.00 - 236400.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

1-3 years of experience training, deploying, and scaling ML/AI models in production environments
Strong experience with distributed systems and ML operations — from large-scale training to low-latency serving and monitoring
Proficiency in Python and modern ML frameworks (e.g., PyTorch), with the ability to implement and optimize complex models
Hands-on experience building or scaling ML/AI infrastructure, pipelines, or reusable platforms that support multiple teams
Curiosity and drive to experiment with advanced AI techniques (e.g., embeddings, retrieval, generative modeling) while staying grounded in production impact
Ability to thrive in a collaborative environment, working with both technical and non-technical partners to drive measurable outcomes

Job Responsibility

Building and scaling advanced ML/AI systems that power core Plaid products and applications used by millions of consumers
Driving impact at scale by improving distributed training, serving, and ML operations to make Plaid’s AI capabilities faster, more reliable, and more widely available
Developing new AI applications that enable innovative product experiences across fintech
Tackling 0 to 1 problems where you explore new approaches, as well as scaling 1 to 10 systems for reliability and efficiency
Collaborating with some of the strongest MLEs at Plaid in a high-ownership, bottom-up driven team
Experimenting with cutting-edge ML and AI techniques while balancing practical productionization and measurable business impact

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

Machine Learning Research Engineer

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

Have 5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets, with 1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime

Senior Machine Learning Engineer

Groupon is a marketplace where customers discover new experiences and services e...

Location

Spain , Madrid; Valencia

Salary:

Not provided

Groupon

Expiration Date

Until further notice

Requirements

5–8+ years hands-on experience building and deploying ML models in production, ideally for recommender, ranking, or personalization systems
Expertise in Python (and optionally Java/Scala), ML frameworks (PyTorch, TensorFlow, XGBoost), feature engineering, and data transformation
Solid background in cloud (GCP strongly preferred), container orchestration (Docker, Kubernetes), and modern data/feature pipelines
Skilled at structuring ambiguous problems and navigating fast-changing priorities—ready to build with minimal legacy constraints
Comfortable communicating complex technical concepts in clear, remote team environments (professional English)

Job Responsibility

Lead the full ML model lifecycle—feature engineering, model design, training, deployment, monitoring, and ongoing improvement
Architect and implement scalable ranking, retrieval, and personalization models using state-of-the-art ML frameworks (e.g., PyTorch, TensorFlow)
Build robust, production-ready ML data pipelines and infrastructure (Python, GCP, Docker/Kubernetes)
Integrate ML models into high-traffic distributed systems
ensure observability, CI/CD, and real-time performance
Collaborate closely with Product and Data Engineering to deeply understand business needs and translate them into measurable user impact
Set technical standards and mentor less-experienced colleagues as an emerging ML leader in our scale-up environment
Experiment with advanced techniques (embeddings, deep learning, reinforcement learning) and champion an evidence-driven, AI-first culture

What we offer

Greenfield Impact: Architect the backbone of Groupon’s revitalized search and recommendations from the ground up—with your work seen by millions
AI-First Scale-Up Vibe: Join a driven, supportive team amid exciting transformation—where speed, ambition, and technical influence matter
Career Launchpad: Be the ML architect/leader you’ve always wanted to be, with clear pathways to technical or team leadership as we grow
Global Collaboration: Work cross-functionally with international colleagues and senior leadership. EMEA time zone overlap preferred for maximum impact

Software Engineer, Machine Learning

Figma is seeking a versatile and experienced Machine Learning / AI Engineer to j...

Location

United States , San Francisco; New York

Salary:

149000.00 - 350000.00 USD / Year

Figma

Expiration Date

Until further notice

Requirements

5+ years of industry experience in software engineering
3+ years focused on applied machine learning or AI
Strong experience with end-to-end ML model development, including training, evaluation, deployment, and monitoring
Proficiency in Python and familiarity with ML libraries like PyTorch, TensorFlow, Scikit-learn, Spark MLlib, or XGBoost
Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality
Experience mentoring or leading others and contributing to a culture of technical excellence and innovation

Job Responsibility

Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features
Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows
Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance
Work with product engineers to define and deliver impactful AI features across Figma’s platform
Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment
Explore new ideas at the edge of what’s technically possible and help shape the long-term AI vision at Figma

What we offer

equity
health, dental & vision benefits
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 Machine Learning Engineer, Personalization and Recommendations

As a Senior Machine Learning Engineer on the Personalization & Recommendations t...

Location

United States , San Francisco

Salary:

183360.00 - 248000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems
Demonstrated impact improving key metrics such as CTR, retention, or engagement through recommender or search systems in production
Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices — including model registries, feature stores, monitoring, and drift detection
Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, or MMoE, and the ability to apply them to real-world problems
Experience with large-scale embedding models and vector search, including FAISS, ScaNN, or similar systems
Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test outcomes to drive product decisions
Clear, effective communication, collaborating well with product managers, data scientists, engineers, and cross-functional partners
A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability
Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals

Job Responsibility

Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals and content features
Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization
Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training–serving consistency, observability, and robust monitoring
Partner with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experiment designs
Advance evaluation methodologies, contributing to offline metric design (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact
Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments
Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem
Mentor junior and mid-level engineers, supporting technical growth, experimentation rigor, and responsible ML practices
Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture

What we offer

20 vacation days
Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
Employer-sponsored 401k plan with company match
Access to LinkedIn Learning and other resources to support professional growth
Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
40 hours of annual paid time off to participate in volunteer programs of choice

Fulltime

Machine Learning Data Engineer - Systems & Retrieval

Zyphra

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:
January 13, 2026

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Machine Learning Data Engineer - Systems & Retrieval

Zyphra

Location:United States , Palo Alto

Category:IT - Software Development

Contract Type:Not provided

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Job Description:

Job Responsibility:

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Nice to have:

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Job Posted:January 13, 2026

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