AI Research Engineer, Enterprise Evaluations Job at Scale (San Francisco)

Principal Ai Engineer - Enterprise Ai Solutions

Our Mission: At Palo Alto Networks®, we’re united by a shared mission—to protect...

Location

United States , Santa Clara

Salary:

185200.00 - 299475.00 USD / Year

Palo Alto Networks

Expiration Date

Until further notice

Requirements

Bachelor's degree in a related field or equivalent military experience required
12+ years of related experience, or a Master's degree with 8 years of experience, or a PhD with 5 years of experience
Proven expertise in designing and building complex, enterprise-grade AI/ML platforms and applications
Direct hands-on experience with Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI systems
Strong programming skills in languages such as Python, Java, or Go and proficiency in modern AI/ML frameworks (e.g., TensorFlow, PyTorch)
Extensive hands-on experience with distributed systems architecture, streaming data platforms, and cloud AI/ML platforms (e.g., GCP Vertex AI, AWS SageMaker)

Job Responsibility

Lead the applied AI solution design and architecture, breaking down ambiguous business problems into concrete, actionable AI solution designs
Drive the hands-on development and implementation of key AI components, supporting both traditional and Generative AI model development and deployment
Contribute significantly to the detailed design of large-scale, distributed AI/ML systems, ensuring performance, reliability, and security
Proactively collaborate with executive leadership, data science, engineering, and product stakeholders to translate business use-cases into scalable AI solutions
Provide technical leadership and mentorship to other AI/ML engineers, fostering a culture of engineering excellence and hands-on experimentation
Lead the implementation and continuous improvement of MLOps pipelines, including automated model training, versioning, deployment, and monitoring
Champion and enforce design standards, patterns, and best practices for scalable and secure development of AI applications across various teams
Actively research and evaluate cutting-edge AI/ML techniques, algorithms, and models to identify opportunities for platform enhancement and new solution development

What we offer

Restricted stock units
Bonus

Fulltime

Enterprise AI Engineer - Modernization

We’re hiring a Generative AI Engineer for our AI-powered modernization platform ...

Location

India , Chennai, Madurai

Salary:

Not provided

OptiSol Business Solutions

Expiration Date

Until further notice

Requirements

Hands-on experience working with foundation models such as GPT-4, Claude, Llama 3, or Mistral to build real-world AI applications
Strong prompt engineering skills including Chain-of-Thought, Few-Shot Prompting, and Tree-of-Thought reasoning techniques
Ability to design and optimize prompts to improve response accuracy, reduce latency, and control token cost
Experience creating system prompts with structured outputs (JSON or schema-based) and implementing safety guardrails
Understanding of LLM data preparation including dataset cleaning, formatting & tokenization
Exposure to model adaptation or fine-tuning workflows using modern ML pipelines
Working knowledge of machine learning frameworks such as PyTorch or TensorFlow
Hands-on experience designing and implementing end-to-end Retrieval-Augmented Generation (RAG) pipelines
Exposure to vector databases such as Pinecone, Weaviate, Milvus, or Qdrant
Strong understanding of embeddings, semantic search, and re-ranking strategies

Job Responsibility

Design, develop, and deploy Generative AI–powered software solutions
Build robust, scalable Python services integrating Large Language Models (LLMs)
Craft and optimize advanced prompts to enforce accuracy, tone, formatting, and guardrails
Fine-tune and adapt LLMs for domain-specific and business-critical use cases
Architect and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines
Develop autonomous and semi-autonomous AI agents
Integrate LLMs with external APIs, databases, and computation engines
Evaluate and monitor model behavior to detect hallucinations, drift, and quality regressions
Write production-grade, modular Python code and participate in code reviews
Stay current with emerging research, tools, and best practices in Generative AI

Fulltime

Distinguished AI Engineer (Agentic Ai Platform)

Distinguished AI Engineer (Agentic AI Platform). At Capital One, we are creating...

Location

United States , San Francisco, California; McLean, Virginia; New York, New York; San Jose, California; Cambridge, Massachusetts

Salary:

Not provided

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies
At least 8 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
Contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement
Evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs
Contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes
Help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs
Collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend
Accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG
Own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs
Coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences

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
Healthy Body, Healthy Mind
Save Money, Make Money
Time, Family and Advice

Fulltime

Senior Data Scientist – Gen AI Engineer - Assistant Vice President

Location

India , Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
8–12 years of experience as a Data Scientist or equivalent role, with at least 2 years of specialized, hands-on experience in Generative AI, including leading technical development and mentoring teams.
Demonstrable experience across the full lifecycle of production-level GenAI projects — from ideation and prototyping through deployment, monitoring, and ongoing maintenance in live environments.
Expert-level Python proficiency
Scikit-learn, XGBoost, LightGBM
PyTorch
Hugging Face Transformers, LangChain, LlamaIndex, Semantic Kernel
LangGraph, CrewAI, AutoGen
Transformer architectures
RAG patterns

Job Responsibility

Working with financial and enterprise data, applying modern NLP and GenAI techniques to solve business problems.
Designing, refining, and systematizing prompt engineering strategies for large language models (LLMs), including structured prompting, chain-of-thought, and few-shot/zero-shot approaches.
Collaborating with business stakeholders to translate requirements into GenAI-powered solutions.
Developing, testing, and maintaining production-grade Python code for GenAI applications.
Integrating with vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector, Qdrant) for retrieval-augmented generation (RAG) pipelines.
Building, monitoring, and optimizing MLOps/LLMOps pipelines for continuous model deployment and observability.
Researching and evaluating emerging GenAI technologies, frameworks, and best practices to maintain competitive advantage.
Troubleshooting and debugging GenAI models and agentic systems in production, including rapid identification and resolution of issues in real-world deployments.
Communicating complex AI/ML concepts clearly to non-technical stakeholders, translating technical jargon into actionable business terms.
Participating in and leading team meetings, design reviews, and architecture discussions.

Fulltime

Ai Engineer

We are building a new AI / Machine Learning team within an industrial digital or...

Location

Czech Republic , Prague

Salary:

110000.00 - 140000.00 CZK / Year

Apollo Solutions

Expiration Date

Until further notice

Requirements

Degree in Computer Science, AI, Data Science, or related field
5+ years experience in software engineering and AI/ML
2+ years hands-on experience with generative AI
Proven experience deploying and fine-tuning ML models in production
Strong skills in Python (Java / .NET a plus)
Solid understanding of ML, deep learning, and statistical modeling
Experience with cloud platforms and containerization (Docker, Kubernetes)
Familiarity with Agile environments and version control (Git)
Strong collaboration and problem-solving skills

Job Responsibility

Act as a technical lead between business, product, and engineering teams
Translate business needs into scalable AI / ML solutions
Design, fine-tune, deploy, and optimize generative AI models (primarily LLMs)
Develop production-grade machine learning pipelines and algorithms
Work with structured, unstructured, time-series, and text data
Integrate AI/ML models into enterprise digital platforms
Evaluate model performance and continuously improve accuracy and reliability
Stay current with AI/ML research, tooling, and best practices
Document architectures, models, and processes for reuse and scalability

Fulltime

Azure Data Science Platform Engineer (AI)

WFH flexibility! Up to 4 days/week! Global Environment! Competitive salary! We a...

Location

Japan , Tokyo 23 wards

Salary:

7000000.00 - 12000000.00 JPY / Year

Randstad

Expiration Date

February 29, 2028

Requirements

Bilingual proficiency in Japanese and English is preferred (English is a MUST)
Day-to-day communication will primarily be in English, with occasional interaction with Japanese-speaking stakeholders
6+ years of experience in data science, machine learning, advanced analytics, or applied AI, with demonstrated business results
Strong experience taking solutions from development into production and supporting them in live environments
Strong Python programming skills and solid engineering discipline
Experience with GenAI / LLM use cases or solution delivery
Hands-on experience with Azure for deploying, supporting, or operating production workloads
Strong experience with Terraform and Infrastructure as Code in enterprise cloud environments
Experience with CI/CD, GitHub Actions, deployment automation, and DevOps practices
Experience with SRE, MLOps, or LLMOps, particularly in monitoring, incident handling, reliability, and operational support

Job Responsibility

We are looking for a candidate who combines strong data science delivery capability with practical production and operational ownership
This is not a pure research role and not a pure platform role. It is intended for someone who can build business-facing AI/ML solutions and also help ensure those solutions are deployable, stable, and maintainable
The ideal candidate is proactive, technically hands-on, comfortable working independently, and effective in cross-functional enterprise environments.

What we offer

WFH flexibility! Up to 4 days/week!
Global Environment!
Competitive salary!
健康保険
厚生年金保険
雇用保険
土曜日
日曜日
祝日

Fulltime

Sr AI Engineer - Agentic Systems

As a core technical leader within our Agentic AI initiatives, you will shape the...

Location

United States , Anywhere

Salary:

Not provided

Dialpad

Expiration Date

Until further notice

Requirements

8+ years of relevant software engineering experience
Proven track record of technical leadership (as a Senior, Staff, or Principal Engineer) shipping complex, large-scale systems
Strong foundations in scaling distributed systems and production-grade infrastructure
Experience with LLM Platforms: Inference optimization and fine-tuning strategies
Experience with Data & Retrieval: Advanced retrieval systems and memory architectures
Experience with Agent Frameworks like LangChain/LangGraph, CrewAI, or AWS/Google Agent ecosystems
Experience with AI Ops: Evaluation, observability, and safety frameworks for production AI systems
Experience with Real-Time Infrastructure: Streaming infrastructure and voice/conversational AI
Experience with Tool Integration: Tool use, API execution frameworks, and human-in-the-loop validation systems
Operational Excellence: Experience setting clear technical goals, identifying architectural risks, and systematically clearing tech-debt gaps

Job Responsibility

Drive Technical Strategy: Own the architectural roadmap and delivery of Dialpad’s Agentic infrastructure, core orchestration layers, memory architectures, and evaluation/observability systems
Build & Scale: Design and deploy scalable, multi-modal AI agents capable of autonomous support, real-time voice reasoning, and secure API tool execution across complex enterprise workflows
Mentor & Influence: Act as a technical anchor for the organization, raising the engineering bar, mentoring senior peers, and defining technical standards for an AI-native SDLC
Partner Cross-Functionally: Collaborate with leadership across Product, Engineering, and Applied Research to align technical execution with Dialpad’s long-term business strategy
Push the Frontier: Research and implement emerging agent frameworks, LLM inference optimization, advanced retrieval systems, and cutting-edge safety/policy guardrails to keep Dialpad at the absolute forefront of the era of the agent

What we offer

Competitive salary
Comprehensive benefits
Real opportunities for growth
Cutting-edge AI tools
Robust training program
Inclusive office environment

Fulltime

Ai Engineer (Corp Functions & Supply Chain)

We are currently seeking a AI Engineer (Corp Functions & Supply Chain) to join o...

Location

United States , Dallas

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Education: Bachelor's or Master's degree in Computer Science, Data Science, Operations Research, or a related technical field
Programming & Tech Stack: 7+ years of high proficiency in languages like Python or Java. Experience with frameworks and libraries such as TensorFlow, PyTorch, LangChain, and LlamaIndex
Enterprise Platforms: 5+ years of familiarity with modern data and ML platforms (e.g., Databricks, Oracle Cloud SCM, AWS, or Azure)
Supply Chain Domain: 3 to 5 years of understanding of Procure-to-Pay, Order-to-Cash, and warehouse/inventory logistics
Compliance with Client's responsible AI principles and Acceptable Use policy
Adherence to data residency, privacy (GDPR, HIPAA where applicable), and 21 CFR Part 11 controls where in scope
Third-party risk assessment and SOC 2 Type II (or equivalent) certification
Disclosure of subcontractors and offshore delivery locations
Disclosure of model providers, training data practices, and any use of client data for model improvement (opt-out required)

Job Responsibility

AI Model Development & Deployment: Build and productionize machine learning algorithms for demand forecasting, inventory optimization, and logistics routing
Corporate & Procurement Optimization: Design GenAI assistants and agents to automate supplier evaluation, negotiation, contract review, and vendor management
Workflow Automation: Deploy Agentic AI to enable autonomous decision-making—such as auto-rerouting shipments during a supply disruption or updating your Enterprise Resource Planning (ERP) without human intervention
System Integration & Architecture: Create RAG pipelines and integrate AI models into existing enterprise systems (like Oracle Cloud, SAP, or AWS/Azure) so that AI recommendations flow directly into business execution
Monitoring & Guardrails: Establish continuous performance metrics and guardrails to ensure AI models remain accurate, cost-effective, and aligned with enterprise safety standards

Fulltime

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AI Research Engineer, Enterprise Evaluations

Job Description

Job Responsibility

Requirements

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