Senior AI Scientist (Agentic AI) Job at Delivery Hero (Berlin)

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Senior Lead Ai Engineer (Mlx, Agentic Ai, Gen Ai Platform Services)

Location

United States , San Francisco; New York; San Jose; Cambridge; McLean

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
At least 6 years of experience programming with Python, Go, Scala, or Java

Job Responsibility

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Fulltime

Senior Data Scientist, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , Bay Area

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

Senior Data Scientist - Agentic Systems

The Global Marketing Engines and Experiences (E&E) team within Microsoft is resp...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience

Job Responsibility

AI-Native Operations
Design, build, and ship agentic capabilities that make the analytics team more AI-native, including co-PM agents that triage incoming work, monitor data science workstreams in Azure DevOps, and propose ticket updates that keep our backlog accurate without manual hygiene effort
Build PM-layer agents that read across the Azure Dev Ops (ADO) portfolio to surface risk, estimate effort on new requests, and recommend project plans that managers can adapt rather than write from scratch
Establish shared infrastructure and patterns — prompting, evaluation, orchestration, observability, guardrails — that let the rest of the team build downstream agents reliably
Analyst Delivery Acceleration
Develop LLM-powered internal tools and skills that compress the cycle from analytics request to delivered insight, including capabilities that draft, format, and pressure-test the standard inputs analysts produce for MBR, MMR, and leadership review rhythms
Identify the highest-friction parts of the analyst delivery flow and design generative AI interventions that remove rather than relocate the work
Partner with the analytics team to instrument adoption, measure time saved, and iterate based on real usage rather than projected value
Marketer-Facing Capabilities
Lead the design and delivery of marketer-facing generative AI capabilities, anchored by a conversational analytics agent that allows marketers across Brand, Product Marketing Management (PMM), Customer Insights, and demand generation to self-serve on the analytics questions they bring to the team today

What we offer

Eligible for benefits and other compensation

Fulltime

Senior Data Scientist, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , New York

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

Senior Data Scientist – AI & ML | MLOps Enablement

The Developer Platform Organization’s mission is to accelerate the delivery of r...

Location

United States , Seattle

Salary:

166000.00 - 258000.00 USD / Year

Nordstrom

Expiration Date

Until further notice

Requirements

Bachelor’s, Master’s, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required
10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models
Deep expertise in model evaluation — defining metrics, thresholds, and evaluation pipelines for real-world production models
Experience with Feature Store design, feature engineering, and understanding of feature freshness, reuse, and drift across different model families
Proficiency in Python with experience writing clean, maintainable, production-quality ML code
Strong understanding of ML monitoring — data drift, prediction drift, and concept drift detection
Experience with experiment tracking and model lifecycle management
Ability to translate between DS practice and platform engineering — comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews
Self-directed
comfortable owning POC work end-to-end without a dedicated DS team structure

Job Responsibility

Run end-to-end POC validation for new platform capabilities — Feature Store, Endpoints, Model Evaluation, AutoML, BigQuery ML etc. — independently, before they reach DS teams at scale
Attend DS team planning and design sessions as an embedded practitioner
surface real workflow pain points and translate them into reusable MLOps platform requirements
Design and own the Model Evaluation Framework — defining metrics, thresholds, and evaluation pipelines for batch, online, and streaming use cases on Vertex AI
Build model-type-aware Feature Store schemas, endpoint configurations, and evaluation pipelines that accommodate the fundamentally different needs of different ML models
Lead benchmarking of Nordstrom’s platform against industry standards — SageMaker vs. Vertex AI — across feature parity, cost, and DS practitioner ergonomics
Author DS-native documentation, onboarding guides, and quickstart notebooks that lower the adoption barrier for new platform features
Contribute DS domain expertise to the emerging Vertex AI Agentic Platform — identifying DS workflow pain points as agent use cases and defining evaluation frameworks for agentic responses
Own model card standards — capturing what actually matters to a practitioner, not just governance checkboxes
Communicate complex trade-offs and platform decisions to technical and non-technical stakeholders across DS, engineering, and leadership

What we offer

Medical/Vision
Dental
Retirement
Paid Time Away
Life Insurance
Disability
Merchandise Discount
EAP Resources
401k
performance-based incentives/bonuses

Fulltime

Senior Data Scientist / AI Consultant – Security & Risk Analytics

Senior Data Scientist / AI Consultant – Security & Risk Analytics. Hybrid – 3 da...

Location

Ireland , Dublin 18

Salary:

100000.00 EUR / Year

Solas IT Recruitment

Expiration Date

Until further notice

Requirements

Proven experience delivering end-to-end ML and DL solutions in production environments
8+ years commercial experience
Strong programming skills in Python and solid SQL expertise
Experience with Generative AI, including LLMs, RAG, vector databases, and agent-based frameworks
Strong analytical thinking with the ability to communicate insights to both technical and non-technical stakeholders
Hands-on experience in data preparation, feature engineering, and model evaluation
A proactive and solution-oriented mindset, comfortable working in fast-paced environments

Job Responsibility

Translate complex business challenges into data-driven solutions using ML, DL, and GenAI techniques
Manage the full model lifecycle including data exploration, feature engineering, modelling, validation, and deployment
Build classification and scoring models, effectively handling incomplete or ambiguous datasets
Develop explainable AI outputs to support business decision-making
Deploy and monitor models to ensure performance, scalability, and reliability
Prototype new concepts and evaluate emerging tools and frameworks
Collaborate with engineering and product teams to deliver scalable, production-ready systems
Support data pipelines, cloud platforms, and CI/CD processes for analytics workloads

What we offer

Excellent salary package
Great benefits
Very good career progression

Fulltime

Senior AI Research Scientist

Workato transforms technology complexity into business opportunity. As the leade...

Location

United States , San Francisco

Salary:

Not provided

Workato

Expiration Date

Until further notice

Requirements

MS/PhD in Computer Science, ML, or related field—or equivalent experience
Hands‑on with PyTorch/JAX and modern LLM frameworks
Strong publication record in top-tier ML venues (NeurIPS, ICML, ICLR) or demonstrable impactful experimental work
hands‑on experience with large‑scale model training, transformer architectures, reinforcement‑learning techniques, and CUDA
Curiosity‑driven and self‑directed
Ability to explain complex ideas to non‑experts
Team player who welcomes feedback and knowledge‑sharing

Job Responsibility

Explore workflow‑aware planning, cost‑optimised RAG, tool‑use evaluation, and multi‑agent collaboration
Prototype and benchmark models
present findings internally and externally
Collaborate with Product & Engineering to ship research‑backed features
Contribute to open‑source repos and author technical blogs

What we offer

vibrant and dynamic work environment
multitude of benefits they can enjoy inside and outside of their work lives

Senior AI Applied Scientist

As a Senior AI Applied Scientist for (insert specific team within BIC), you will...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, Statistics, Electrical/Computer Engineering, Physics, Mathematics or related field AND 4+ years of experience in AI/ML, predictive analytics, or research
OR Master’s degree AND 3+ years of experience
OR PhD AND 1+ year of experience
OR equivalent experience
1+ years of experience with generative AI OR LLM/ML algorithms
Ability to meet Microsoft, customer, and/or government security screening requirements
This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter

Job Responsibility

Build collaborative relationships with product and business groups to deliver AI-driven impact
Research and implement state-of-the-art using foundation models, prompt engineering, RAG, graphs, multi-agent architectures, as well as classical machine learning techniques
Fine-tune foundation models using domain-specific datasets
Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments, and ROI analysis
Build rapid AI solution prototypes, contribute to production deployment of these solutions, debug production code, and support MLOps/AIOps
Contribute to papers, patents, and conference presentations
Translate research into production-ready solutions and measure their impact through A/B testing and telemetry that address customer needs
Ability to use data to identify gaps in AI quality, uncover insights, and implement PoCs to show proof of concepts
Demonstrate deep expertise in AI subfields (e.g., deep learning, Generative AI, NLP, muti-modal models) to translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact
Share insights on industry trends and applied technologies with engineering and product teams

Fulltime

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Senior AI Scientist (Agentic AI)

Job Description

Job Responsibility

Requirements

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What we offer

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