data engineer

ai engineer

machine learning engineer

senior ai engineer

platform engineer

machine learning architect

NewRocket

<div><p><b>Agentic AI Architect-Anthropic Partnership</b></p>
<p><b>
Why Us</b></p>
<p>
NewRocket is proud Anthropic partner/vendor, expanding our ability to help enterprises responsibly adopt and operationalize Claude-powered AI solutions. Through this relationship, NewRocket is building advanced capabilities in generative AI, agentic workflows, secure enterprise knowledge experiences, and AI-enabled automation. Our teams apply Anthropic-aligned practices in prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, model evaluation, safety, governance, and human-in-the-loop controls.</p>
<p>
For an Agentic AI Architect, this partnership represents an opportunity to work at the forefront of enterprise AI&mdash;designing scalable, secure, and high-value solutions that connect Claude and other AI technologies with ServiceNow, enterprise data, business processes, and mission-critical workflows.</p>
<p>
NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence.</p>
<p>
Travel to clients and conferences as needed.</p>
<p><b>
We #GoBeyondWorkflows to create new kinds of experiences for our customers.</b></p>
<p><b>
Come join our Crew!</b></p>
<p><b>
The Role</b></p>
<p>
NewRocket is hiring an experienced Agentic AI Architect to support a large global client and help shape, design, and deploy enterprise AI solutions.</p>
<p>
This role combines AI/ML architecture, generative AI engineering, data engineering, cloud solution design, and technical leadership. You will be responsible for defining scalable architectures for AI and machine learning applications, including predictive analytics, natural language processing, retrieval-augmented generation (RAG), intelligent automation, and agentic AI systems.</p>
<p>
The ideal candidate brings strong hands-on expertise in Python, SQL, cloud services, databases, big-data technologies, and modern machine learning frameworks. You will also have practical experience designing LLM-powered applications that safely connect models to enterprise knowledge, systems, APIs, and workflows.</p>
<p>
You will work closely with client stakeholders, NewRocket consultants, ServiceNow teams, data engineers, and AI/ML engineers to translate business needs into secure, reliable, and production-ready AI solutions.</p>
<p><b>
We are #GoingBeyond. Come join our Crew!</b></p>
<p><b>
</b></p><p><b>What You Will Be Doing</b></p>
<p>
AI/ML Architecture &amp; Solution Delivery</p>
<ul>
<li>Architect, develop, deploy, and maintain scalable AI and machine learning solutions for enterprise use cases.</li>
<li>Define end-to-end solution architectures spanning data ingestion, data preparation, model selection, orchestration, APIs, workflow integrations, user experiences, monitoring, and governance.</li>
<li>Partner with business and technical stakeholders to identify high-value AI opportunities and translate requirements into actionable technical designs and delivery roadmaps.</li>
<li>Design solutions for predictive analytics, classification, clustering, forecasting, anomaly detection, recommendation, and intelligent automation.</li>
<li>Establish technical standards, reference architectures, reusable patterns, and best practices for enterprise AI delivery.</li>
<li>Lead technical discovery, architecture workshops, design reviews, proof-of-concepts, and client demonstrations.</li>
</ul>
<p><b>Generative AI, Anthropic &amp; LLM Engineering</b></p>
<ul>
<li>Design and implement enterprise generative AI applications using Claude, the Anthropic API, and other LLM platforms when appropriate for the business use case.</li>
<li>Apply effective prompt and context-engineering practices, including instruction design, few-shot examples, role definition, structured inputs and outputs, response constraints, and long-context management.</li>
<li>Architect retrieval-augmented generation (RAG) solutions that securely ground model outputs in approved enterprise documents, knowledge bases, databases, and other data sources.</li>
<li>Design document ingestion, chunking, embedding, vector search, retrieval, reranking, citation, and response-generation patterns for enterprise knowledge workflows.</li>
<li>Build and integrate AI capabilities using structured outputs, tool use/function calling, APIs, and workflow orchestration.</li>
<li>Assess and recommend the appropriate balance of LLMs, traditional machine learning, deterministic automation, enterprise search, and human decision-making for each use case.</li>
<li>Stay current on Anthropic platform capabilities, Claude releases, Anthropic implementation guidance, responsible AI principles, and enterprise AI best practices.</li>
<li>Complete relevant Anthropic partner enablement, technical training, and product education as available through NewRocket's partnership.</li>
<li>Travel to clients and conferences as needed.</li>
</ul>
<p><b>Agentic AI &amp; Workflow Orchestration</b></p>
<ul>
<li>Architect and implement agentic AI systems that can reason over enterprise context, use authorized tools, execute multi-step tasks, and coordinate work across enterprise applications.</li>
<li>Design AI agents with defined roles, task boundaries, tool permissions, memory and context strategies, approval gates, fallback paths, and escalation mechanisms.</li>
<li>Develop agentic workflows that integrate with ServiceNow, enterprise APIs, cloud services, databases, collaboration platforms, and operational systems.</li>
<li>Implement human-in-the-loop controls for sensitive, high-impact, low-confidence, or exception-based actions.</li>
<li>Design safeguards to prevent unintended tool execution, unauthorized data access, prompt injection, unsafe outputs, and uncontrolled autonomous behavior.</li>
<li>Evaluate agent effectiveness through task-completion rates, quality, reliability, latency, cost, safety, and user-adoption measures.</li>
</ul>
<p><b>Machine Learning, NLP &amp; Data Science</b></p>
<ul>
<li>Develop, train, validate, deploy, and monitor machine learning models for predictive analytics, classification, clustering, and related use cases.</li>
<li>Implement AI and ML solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Develop NLP capabilities using Hugging Face transformer models and cloud AI services for text classification, summarization, sentiment analysis, entity extraction, and document intelligence.</li>
<li>Evaluate, adapt, and where appropriate fine-tune open-source or client-approved models for targeted use cases; apply prompt engineering, RAG, and tool use as preferred strategies when model fine-tuning is not appropriate or available.</li>
<li>Work with large language models for conversational AI, text generation, summarization, knowledge assistance, workflow automation, and decision support.</li>
<li>Build data-processing and feature-engineering pipelines that support reliable model training, testing, deployment, and monitoring.</li>
</ul>
<p><b>Cloud, Data Engineering &amp; Platform Integration</b></p>
<ul>
<li>Design and implement AI solutions using cloud platforms including AWS (e.g., SageMaker, Lambda, S3), Microsoft Azure, and Google Cloud Platform (e.g., Vertex AI).</li>
<li>Develop integrations between AI services, ServiceNow, enterprise applications, APIs, identity providers, databases, document repositories, and data platforms.</li>
<li>Build supporting services, APIs, microservices, automation logic, and integration components required to operationalize AI solutions.</li>
<li>Work with big-data technologies such as Apache Spark and Snowflake for large-scale data processing, analytics, and AI data pipelines.</li>
<li>Design and optimize ETL/ELT pipelines for data ingestion, transformation, validation, quality management, governance, and observability.</li>
<li>Use SQL, MySQL, PostgreSQL, MongoDB, and comparable technologies for data modeling, database management, query optimization, and data warehousing.</li>
<li>Apply secure engineering practices for authentication, authorization, secrets management, encryption, logging, error handling, and access controls.</li>
</ul>
<p><b>AI Quality, Governance &amp; Responsible AI</b></p>
<ul>
<li>Establish evaluation frameworks, test suites, representative datasets, and regression-testing practices for AI, ML, and agentic solutions.</li>
<li>Measure and optimize solution quality across relevance, accuracy, groundedness, safety, task completion, model behavior, latency, cost, reliability, and user experience.</li>
<li>Implement observability, monitoring, tracing, alerting, and feedback loops for production AI applications.</li>
<li>Define practical governance approaches for data privacy, sensitive-data handling, model access, auditability, model limitations, and responsible AI usage.</li>
<li>Implement controls for role-based access, data permissions, grounded responses, source attribution, output validation, exception handling, and human review.</li>
<li>Document architecture decisions, AI-system behavior, limitations, risk controls, operating procedures, and support requirements.</li>
</ul>
<p><b>ServiceNow, Automation &amp; Enterprise Experience</b></p>
<ul>
<li>Design AI-enabled workflow automations and intelligent experiences within ServiceNow and connected enterprise ecosystems.</li>
<li>Support chatbot, virtual-agent, employee-support, customer-service, IT operations, knowledge-management, and workflow-automation use cases.</li>
<li>Integrate AI solutions with ServiceNow capabilities such as workflow automation, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, knowledge management, and enterprise data sources, where applicable.</li>
<li>Develop AI automation solutions using collaboration platforms and cloud AI services, including Microsoft Teams and Azure AI, where appropriate.</li>
<li>Contribute reusable implementation patterns, agent designs, integration components, evaluation assets, and accelerators that strengthen NewRocket's AI Foundry capabilities.</li>
</ul>
<p><b>Analytics &amp; Visualization</b></p>
<ul>
<li>Create interactive data visualizations and executive-ready reporting using tools such as Tableau and Power BI.</li>
<li>Develop dashboards and measurement frameworks that help stakeholders understand AI adoption, workflow outcomes, business value, operational performance, and model quality.</li>
<li>Support the definition and tracking of KPIs that demonstrate measurable value from AI-enabled solutions.</li>
</ul>
<p></p><p><b>What You Bring Along</b></p>
<ul>
<li>10+ years of experience applying AI, machine learning, data science, software engineering, or intelligent automation technologies to practical enterprise use cases.</li>
<li>Strong coding expertise in Python and SQL, with hands-on experience using ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.</li>
<li>Demonstrated experience architecting or delivering AI/ML, LLM, RAG, conversational AI, agentic AI, or AI-powered automation solutions.</li>
<li>Strong understanding of algorithms, object-oriented programming, functional design principles, software architecture, and API-based integration patterns.</li>
<li>Hands-on experience with LLM concepts and application-development patterns, including prompt engineering, context management, tokens, embeddings, vector search, RAG, tool use, structured outputs, and model evaluation.</li>
<li>Proficiency with data-science libraries such as Pandas, NumPy, Matplotlib, and Seaborn.</li>
<li>Hands-on experience with cloud platforms such as AWS, Azure, and/or Google Cloud.</li>
<li>Experience with big-data processing and cloud data platforms, including Apache Spark and Snowflake.</li>
<li>NLP experience using Hugging Face, transformer models, cloud AI services, or comparable technologies.</li>
<li>Strong understanding of database management, query optimization, data warehousing, ETL/ELT pipelines, and data-quality practices.</li>
<li>Experience with data visualization tools such as Tableau and Power BI.</li>
<li>Knowledge of responsible AI practices, including privacy, security, human oversight, hallucination mitigation, prompt-injection defenses, model limitations, and governed deployment.</li>
<li>Strong analytical, architectural, problem-solving, communication, and stakeholder-management skills.</li>
<li>Ability to collaborate effectively across client, consulting, engineering, product, data, and AI/ML teams.</li>
<li>Ability to learn and adapt quickly as AI technologies, enterprise requirements, and client needs evolve.</li>
</ul>
<p></p><p><b>Preferred Qualifications</b></p>
<p><b>
Anthropic &amp; Claude Experience</b></p>
<ul>
<li>Hands-on experience with Claude, the Anthropic API, Anthropic Console, Claude Code, or Anthropic-focused implementation guidance.</li>
<li>Completion of Anthropic Academy courses, partner enablement, technical training, or equivalent experience building Claude-powered enterprise applications.</li>
<li>Experience using Claude capabilities such as long-context processing, document analysis, tool use, structured outputs, and enterprise knowledge workflows.</li>
<li>Familiarity with Model Context Protocol (MCP) concepts and secure patterns for connecting AI applications to enterprise tools and data sources.</li>
</ul>
<p><b>Agentic AI &amp; LLM Operations</b></p>
<ul>
<li>Experience designing AI agents, multi-agent systems, AI orchestration workflows, and human-in-the-loop operating models.</li>
<li>Experience with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable frameworks.</li>
<li>Experience with vector databases, semantic retrieval, enterprise search, embeddings, document ingestion, reranking, and RAG evaluation.</li>
<li>Familiarity with AI observability, tracing, prompt/version management, evaluation frameworks, guardrails, model monitoring, and cost optimization.</li>
<li>Experience with MLOps, LLMOps, CI/CD, Docker, Kubernetes, infrastructure as code, and production cloud deployment practices.</li>
</ul>
<p></p><p><b>Education</b></p>
<ul>
<li>Bachelor's degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, Engineering, or a related technical field; equivalent relevant experience will also be considered.</li>
<li>Advanced degree or relevant AI, cloud, data, ServiceNow, or Anthropic certifications are a plus.</li></ul><br>
<p></p>
<p>
</p><p><b>We Take Care of Our People</b></p>
<p>
NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.in@newrocket.com.</p></div>

Agentic AI Architect-Anthropic-UK

Blue Yonder

<div><h2 class="jobSectionHeader"><b>End-to-End Principal Architect - WMS</b></h2><p></p><p>
Job Profile Summary<br>
E2E Principal Architect is a self-driven associate who will lead the end-to-end implementation of large footprint Blue Yonder solutions for Warehouse Management Solutions starting with the overall architecture of the solution, partnering with all key stakeholders to drive the implementation of all the multiple business releases within the program, be the single point of contact for all customer business stakeholders on the overall solution footprint.</p><p></p><h3 class="jobSectionHeader"><b>
Job Description</b></h3><p></p><p><b>
Overview</b></p><p>
The End-to-End Principal Architect will work within the Consulting Services team at Blue Yonder to lead and manage the end-to-end solution design and implementation of Cognitive Execution Solutions, and Cognitive Warehouse Management Solutions for clients. The End-to-End Principal Architect will be responsible for ensuring project success by effectively communicating with clients, managing project timelines, and leading solution teams as part of a project. They will be accountable for the overall functional and technical designs, implementation and delivery of end-to-end solutions, and will work closely with the clients and the project teams to ensure that the solutions align with the client's business objectives and meet their requirements.</p><p></p><p><b>
Our current technical environment</b></p><p>
We leverage SaaS microservices and various Blue Yonder solutions and integrate with client solutions and landscapes.</p><p></p><p><b>
What you will do:</b></p><ul><li>
Serve as the primary point of contact for clients throughout the project lifecycle</li><li>
Develop and manage project timelines and budgets</li><li>
Lead solution teams and ensure project deliverables meet client expectations</li><li>
Lead integration of the core product to develop solutions utilizing Platform</li><li>
Identify and manage project risks and issues</li><li>
Act as an internal consultant to other teams within Blue Yonder</li><li>
Design and implement end-to-end solutions based on client requirements and best practices</li><li>
Provide functional and technical guidance and mentorship to junior team members</li><li>
Continuously evaluate and improve solution processes and tools utilizing the latest technologies, i.e. Agentic AI, Machine Learning</li><li>
Work closely with the clients and other project teams to ensure that the solutions align with the client's business objectives and meet their technical requirements.</li><li>
Collaborate with the project managers, delivery partners, and other stakeholders to ensure that the solutions are delivered on-time, on-budget, and to the client's satisfaction.</li></ul><p></p><p><b>
What we are looking for (Team Specific Qualifications &amp; Education):</b></p><ul><li>
15 + years of experience in solution architecture and consulting or a related field</li><li>
Expertise in designing and implementing Blue Yonder (micro service based) Warehouse Management solutions</li><li>
Expertise in designing and implementing at least one other Execution solution &ndash; Warehouse Labour Management, Transportation Management, Order and/ or Returns Management</li><li>
Proven experience leading and managing solution projects</li><li>
Strong communication, interpersonal and presentation skills to be able to interact with customer at all levels, from CIO and Senior Supply Chain Leader downward.</li><li>
Ability to think strategically and solve complex problems</li><li>
Strong technical skills in one or more areas such as cloud infrastructure, software development, data engineering, and data analytics.</li><li>
Experience with project management tools and methodologies</li><li>
Strong ability to work in a fast-paced and dynamic environment</li><li>
Strong understanding of the software development life cycle and experience with Agile methodologies.</li><li>
Experience working with Supply Chain, logistics, retail and manufacturing industries would be a plus.</li></ul><p></p><p><b>
Our Values</b></p><p><br>
If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success &ndash; and the success of our customers. Does your heart beat like ours? Find out here: Core Values</p><p></p><p>
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.</p></div>

Principal Architect (E2E) - WMS

Helsing

<div>
 <strong>
  Who We Are
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  <br/>
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 Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.
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 As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.
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 We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams &ndash; and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.
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 <strong>
  The role
  <br/>
  <br/>
 </strong>
 At Helsing, we are pioneering the future of autonomous decision-making for defence. Our work spans the full AI landscape, including high-volume data processing, RL agent training, and large-scale foundation models. As a member of a cross-functional team, you will architect and implement the tools and platforms that enable these breakthroughs. Your focus will be on abstracting complex distributed systems to maximise training throughput and developer velocity. We are looking for engineers who can navigate the convergence of machine learning and systems engineering to build robust, scalable platforms.
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  What you will do:
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   Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases.
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   Scale our current infrastructure and tooling stack to support faster and larger distributed training.
  </li>
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   Design data strategy to support large scale datasets and efficient storage, ensuring GPUs stay warm.
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   <br/>
  </li>
 </ul>
 <strong>
  You should apply if you:
  <br/>
  <br/>
 </strong>
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  <li>
   Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning.
  </li>
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   Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don&rsquo;t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.
  </li>
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   Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.
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   Have a "first-principles" mindset: you enjoy reading the latest AI optimisation blog posts and integrating them into codebases rapidly.
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   You have debugged production ML pipelines and can tell a good war story about finding a subtle numerical or performance issue.
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  Note: We operate at an intersection where women, as well as other minority groups, are systematically
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  Nice to have
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   You have hands-on experience training models on large-scale GPU clusters, implementing advanced parallelism strategies, and understanding the underlying cross-node communication patterns (NCCL, MPI).
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   You have worked with large-scale datasets made of different modalities. Understanding the tradeoffs in locality, encoding, formats, and streaming strategies.
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   You are proficient with workload orchestrators like Slurm, Kubernetes, or Ray, having used them to schedule and manage complex, concurrent training jobs at scale.
  </li>
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   You understand GPU architecture at a low level: memory hierarchies, warp execution, and what makes a GPU suited for training versus inference workloads.
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  </li>
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  Join Helsing and work with world-leading experts in their fields
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  <li>
   Helsing&rsquo;s work is important. You&rsquo;ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns.
  </li>
  <li>
   The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world.
  </li>
  <li>
   Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward.
  </li>
  <li>
   In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.
  </li>
  <li>
   We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn&rsquo;t work, and to take ownership of aspects of our culture that you care deeply about.
   <br/>
   <br/>
  </li>
 </ul>
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  What We Offer
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   Competitive salary and VSOP options
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   Relocation support: up to &euro;2,500 and 4 weeks temporary accommodation
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   Learning: &euro;500/&pound;450 yearly allowance
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   Health &amp; wellness: gym membership and mental health support (Nilo.health)
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   Social: regular company events and monthly social allowances
  </li>
  <li>
   Enhanced parental leave: 22 weeks fully paid for primary caregivers &amp; 6 weeks for secondary caregivers
  </li>
  <li>
   Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work
  </li>
  <li>
   A hands-on onboarding program (affectionately labelled &ldquo;AI-duction&rdquo;), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one
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   <br/>
  </li>
 </ul>
 <em>
  These are the core benefits across all locations, there may be additional benefits in certain locations.
  <br/>
  <br/>
 </em>
 <em>
  Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.
  <br/>
  <br/>
 </em>
 Helsing's Candidate Privacy and Confidentiality Regime can be found here.
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</div>


AI Research Engineer - ML Engineering

Databricks

<div><p><b>The Role</b></p>
<p>As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present&mdash;combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.</p>
<p><b>The Impact You Will Have</b></p>
<ul><li>Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning</li>
<li>Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins</li>
<li>Own frontline technical relationships with customer engineers, data teams, and technical leads</li>
<li>Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption</li>
<li>Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations</li>
<li>Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community</li>
</ul><p><b>What We Look For</b></p>
<ul><li>4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role</li>
<li>Proficient in Python and PySpark/Spark with demonstrated ability to debug, optimize, and write production-quality code &mdash; live coding is a required interview stage</li>
<li>Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)</li>
<li>Working knowledge of distributed data systems: Apache Spark&trade;, Delta Lake, or equivalent (Hadoop, Kafka, Flink)</li>
<li>Experience leading technical customer conversations &mdash; discovery, whiteboarding, architecture reviews</li>
<li>Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics</li>
<li>Strong presentation and demo skills &mdash; you will build and present a live solution during the interview</li>
<li>Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)</li><br>
</ul><p><br>
<b>Nice to Have:</b></p>
<ul><li>Databricks certification or experience with the Databricks Platform</li>
<li>Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow</li>
<li>Background at a data/AI company, cloud provider, or technical consulting firm</li>
</ul><p><b>Interview Process:</b> Recruiter Screen Hiring Manager Screen Design and Architecture Interview Live Coding Assessment Build, Demo, Pitch! Presentation Reference Check</p><br>
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<div><p><b>About Databricks</b></p>
<p>Databricks is the Data and AI company. More than 20,000 organizations worldwide &mdash; including adidas, AT&amp;T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 &mdash; rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
<br>
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<b>Benefits
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At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.<br>
<br>
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</p><p><b>Our Commitment to Diversity and Inclusion</b></p>
<p>At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.</p>
<p><b>Compliance</b></p>
<p><b>If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</b></p></div></div>

Sr. Solutions Engineer

Autodesk

<div>
 <strong>
  Job Requisition ID #
  <br/>
  <br/>
 </strong>
 26WD100236
 <br/>
 <br/>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  Position Overview
  <br/>
  <br/>
 </strong>
 The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world.
 <br/>
 <br/>
 As a Machine Learning Engineer at Autodesk Research, you will work side-by-side with researchers and engineers to build and enable ML-powered capabilities in Autodesk products. You are an ML engineer with strong software engineering skills who is passionate about solving problems and building things, and excited to collaborate with AI researchers to implement generative AI features. You will operate in a fast-moving, research-driven environment where problems are often not fully defined, requiring strong problem framing and rapid iteration.
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 <br/>
 The team work in a hybrid working model from our offices in London.
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 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Collaborate on projects at the intersection of research and product with a diverse, global team
  </li>
  <li>
   Build and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental models
  </li>
  <li>
   Work with complex datasets and representations for model training, evaluation, and analysis
  </li>
  <li>
   Analyze errors and provide solutions to problems
  </li>
  <li>
   Present results to collaborators and leadership
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Minimum Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BSc or MSc in Computer Science, or equivalent industry experience
  </li>
  <li>
   3+ years of machine learning experience
  </li>
  <li>
   Experience working in research or experimental environments with evolving requirements
  </li>
  <li>
   Proficiency with modern deep learning libraries and frameworks (PyTorch, HuggingFace)
  </li>
  <li>
   Experience with computational geometry and 3D data (e.g., meshes, B-Rep models)
  </li>
  <li>
   Experience working with diverse data representations, including 2D and 3D geometry
  </li>
  <li>
   Experience with version control, reproducibility, and deploying machine learning models
  </li>
  <li>
   Experience using modern AI/GenAI tools in development or experimentation workflows
  </li>
  <li>
   Excellent written documentation skills
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or related field
  </li>
  <li>
   Experience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)
  </li>
  <li>
   Experience with cloud services and architectures (e.g. AWS, Azure)
  </li>
  <li>
   Experience with LLMs or generative AI systems (fine-tuning, prompting, evaluation)
  </li>
  <li>
   Knowledge of the design, manufacturing, AEC, or media &amp; entertainment industries
  </li>
  <li>
   Experience with Autodesk or similar products (CAD, CAE, CAM, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Learn More
   <br/>
   <br/>
  </strong>
 </strong>
 <strong>
  About Autodesk
  <br/>
  <br/>
 </strong>
 Welcome to Autodesk! Amazing things are created every day with our software &ndash; from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
 <br/>
 <br/>
 We take great pride in our culture here at Autodesk &ndash; it&rsquo;s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
 <br/>
 <br/>
 When you&rsquo;re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
 <br/>
 <br/>
 <strong>
  Salary transparency
  <br/>
  <br/>
 </strong>
 Salary is one part of Autodesk&rsquo;s competitive compensation package. Offers are based on the candidate&rsquo;s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
 <br/>
 <br/>
 <strong>
  Belonging
  <br/>
  <br/>
 </strong>
 We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
 <br/>
 <br/>
 <strong>
  Are you an existing contractor or consultant with Autodesk?
  <br/>
  <br/>
 </strong>
 Please search for open jobs and apply internally (not on this external site).
</div>


Machine Learning Engineer 3D Geometry/ Multi-Modal

Gensler

<div><div><div><div><h2 class="jobSectionHeader"><b>General Information</b></h2>
</div></div><div><div><div><div>Posting Date</div>
<div>08-28-2026</div>
</div><div><div>Time Type</div>
<div>Full-Time</div>
</div><div><div>Job ID</div>
<div>8940</div>
</div><div><div>Areas of Expertise</div>
<div>Design Technology</div>
</div><div><div>Job Category</div>
<div>Data Apps</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Locations</b></h2>
</div></div><div><div><div><div>London, United Kingdom</div>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description</b></h2>
</div></div><div></div><div><div><div><div><p>Placed at the heart of Gensler&rsquo;s People + Process + Technology, the Global Design Technology Studio is advancing a growing data and machine learning foundation that is shaping how the firm designs and delivers its work for generations to come. We believe that when the right intelligence is in the hands of the right people at the right moment, we can transform Gensler and our industry so that our designers can make better decisions, unlock new value for clients, and create built environments that are more responsive, more meaningful, and more impactful than ever before.
</p><p>In the role of Machine Learning Engineer, you will drive and operationalize machine learning across AEC data domains including BIM, geospatial, design-performance, operational, and other project and practice data, translating technical capability into tools and workflows that practitioners can use. This is a digitally transformative, hands-on engineering role focused on building, deploying, maintaining, and optimizing machine learning systems and data pipelines, working with large-scale datasets to power production-ready intelligent systems and drive scalable outcomes across the firm. Success in this role means delivering reliable, secure, and well-governed ML systems that integrate into design workflows, are adopted by teams, and improve decision-making across the firm. You will help shape these capabilities inside an established Design Technology team, working alongside AI and data engineers, data scientists, designers, and product stakeholders to translate ambitious, pioneering ideas into production-ready platforms.<br>
</p><p></p><br>
<p><b>What You Will Do
</b></p><div><ul><li>Design, build, and maintain reliable Azure-based ETL/ELT pipelines that deliver clean, documented data to models, APIs, internal applications, dashboards, and Gensler IP.</li>
<li>Own the production ML lifecycle on Azure &mdash; deployment, monitoring, versioning, retraining, rollback, and incident response &mdash; including model registries, feature stores, evaluation frameworks, and benchmarking.</li>
<li>Implement CI/CD, testing, reproducibility, and deployment standards for model and data workflows.</li>
<li>Extend and mature cloud data architecture and modeling strategies that support analytics and machine learning workloads.</li>
<li>Source, profile, and document datasets with business owners to confirm provenance, quality, fitness for use, and alignment with client-data and governance requirements.</li>
<li>Evaluate model performance and address root causes across data quality, feature engineering, training methodology, and architecture.</li>
<li>Translate research prototypes and experimental models into documented, production-ready systems.</li>
<li>Work across AEC data types such as BIM/Revit/IFC, geospatial, design-performance, occupancy, and other built-environment datasets.</li>
<li>Integrate machine learning outputs into design and delivery workflows so practitioners can access insights earlier and make more informed project decisions.</li>
<li>Apply responsible AI and data governance practices, including transparency, traceability, human oversight, and appropriate handling of client and project data.</li>
<li>Support the firm's data-driven design community through technical guidance, code review, and knowledge sharing.</li>
<li>Help define and track success criteria for deployed systems, including reliability, adoption, reuse, and measurable workflow or decision impact.</li><br>
</ul></div><p></p><br>
<p><b>Your Qualifications
</b></p><div><ul><li>Bachelor's or advanced degree in Computer Science, Software Engineering, Data Science, Statistics, Applied Mathematics, or a related field; equivalent production ML or data engineering experience considered.</li>
<li>8+ years of hands-on experience building, deploying, and operating production ML systems on Azure, with practical MLOps and CI/CD experience including experiment tracking, deployment hygiene, monitoring, evaluation, and operational documentation.</li>
<li>Strong Python and software engineering fundamentals, including testing, version control, code review, reproducibility, modular design, documentation, and maintainable code practices.</li>
<li>Strong experience with Azure-based data and ML platforms, ideally including Azure ML, Databricks, Azure Data Factory or Fabric pipelines, Blob/Data Lake storage, and MLflow or similar tooling.</li>
<li>Experience building production-grade ETL/ELT pipelines and supporting ML workloads from ingestion through deployment.</li>
<li>Comfort moving between data engineering, machine learning, cloud architecture, infrastructure, and hands-on data exploration in a creative, collaborative environment.</li>
<li>Practical knowledge of containerization, infrastructure-as-code, and platform and tooling decisions in lean or fast-moving engineering environments.</li>
<li>Clear communicator who can explain technical decisions to non-engineering stakeholders, collaborate across disciplines, and mentor or support junior engineers.</li>
</ul></div><p>Meaningful pluses
</p><div><ul><li>Experience with AEC, real estate, BIM, geospatial, or digital twin data</li>
<li>Experience integrating ML into practitioner-facing workflows</li>
<li>Familiarity with responsible AI practices</li>
<li>LLM or GenAI deployment patterns</li>
<li>Power BI or other visualization tools</li>
<li>Experience with agentic engineering practices</li><br>
</ul></div><p></p><br>
<p><b>Life at Gensler
</b></p><p>At Gensler, we are as committed to enjoying life as we are to delivering best-in-class design. From curated art exhibits to internal design competitions to &ldquo;Well-being Awareness Week,&rdquo; our offices reflect our people&rsquo;s diverse interests.
</p><p>We encourage every person at Gensler to lead a healthy and balanced life. Our comprehensive benefits include medical, dental, vision, disability, wellness programs, flex spending, paid holidays, and paid time off. We also offer a 401k, profit sharing, employee stock ownership, and twice annual bonus opportunities. Our annual base salary range has been established based on local markets.<br>
<br>
</p><p>As part of the firm&rsquo;s commitment to licensure and professional development, Gensler offers reimbursement for certain professional licenses and associated renewals and exam fees. In addition, we reimburse tuition for certain eligible programs or classes. We view our professional development programs as strategic investments in our future.</p><br>
<div></div>
<div></div><br>
<div><b>NOTICE TO APPLICANTS
</b></div><div>We are proud to be an Equal Employment Opportunity and Affirmative Action employer of choice. All aspects of employment decisions will be based on merit, performance, and business needs. We do not discriminate on the basis of any status protected under applicable regulatory laws.
</div><div>Individuals with disabilities and protected veterans are encouraged to apply. We also consider qualified applicants with criminal histories consistent with applicable regulatory laws.
</div><div>Gensler endeavors to make gensler.com/careers accessible to all applicants. If you need assistance or an accommodation due to a disability, you may <b>contact us </b>.
</div><div>Regarding Gensler&rsquo;s approach to recruiting new talent, we will never ask an applicant for sensitive or personal financial information during the recruitment process. We advise all applicants seeking employment with Gensler to review available information on <b>recruitment fraud </b>. Anyone who suspects that they have been contacted by someone falsely representing Gensler should email talentacquisition@gensler.com .</div></div></div></div></div></div></div>

Machine Learning Engineer

International SOS

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We are looking for an experienced Senior Machine Learning Engineer to join our Product team, in Chiswick, West London,
 <br/>
 <br/>
 You will be responsible for building production-grade AI capabilities across the platform&rsquo;s generative and agentic paradigms &ndash; from retrieval-augmented knowledge assistants and context-aware responses to multi-step agent workflows. The role combines strong machine learning and software engineering skills to deliver grounded, governed, and scalable solutions that move from Lab prototype to Factory production.
 <br/>
 <br/>
 This is an excellent opportunity for an experienced engineer, looking for their next move in a global organization.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement ML, generative, and agentic AI solutions &mdash; RAG pipelines, prompt workflows, tool-calling agents, and predictive models
  </li>
  <li>
   Build grounded retrieval over enterprise knowledge with source citation and tenant isolation
  </li>
  <li>
   Integrate models via the model gateway, applying guardrails, PII redaction, and content safety on every request
  </li>
  <li>
   Develop and maintain agent orchestration, memory, and human-in-the-loop escalation paths
  </li>
  <li>
   Perform data preprocessing, feature engineering, prompt design, and evaluation using enterprise datasets
  </li>
  <li>
   Deploy solutions through MLOps/LLMOps pipelines with monitoring, evaluations, and SLAs
  </li>
  <li>
   Optimise models and prompts for accuracy, latency, cost, and groundedness
  </li>
  <li>
   Run experiments, track metrics against golden sets, and iterate to improve quality
  </li>
  <li>
   Collaborate with AIOps and Security to integrate solutions into CI/CD and production monitoring
  </li>
  <li>
   Support responsible-AI practices, model cards, and version control for every release
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About You
  <br/>
  <br/>
 </strong>
 6+ years in AI/ML engineering or applied machine learning
 <br/>
 <br/>
 Strong Python skills with scikit-learn, TensorFlow, PyTorch, or XGBoost, plus experience with LLM frameworks (LangChain/LangGraph) and RAG
 <br/>
 <br/>
 Experience with cloud AI services (AWS Bedrock/SageMaker, Azure, or GCP) and vector stores
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 <br/>
 Proficiency in SQL and working with data warehouses/lakes and embeddings
 <br/>
 <br/>
 Familiarity with MLOps/LLMOps, containerisation (Kubernetes), and CI/CD
 <br/>
 <br/>
 Understanding of prompt engineering, evaluation harnesses, and guardrails
 <br/>
 <br/>
 Strong grasp of ML theory, software engineering practices, and version control (Git)
 <br/>
 <br/>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and incentive scheme
  </li>
  <li>
   Warm, supportive, and open company culture
  </li>
  <li>
   An opportunity to thrive in a global environment
  </li>
  <li>
   Hybrid working: 3 days in the office
  </li>
  <li>
   Birthday holiday and option to purchase additional annual leave
  </li>
  <li>
   Comprehensive Benefits Package: Private Pension, Private Medical Insurance, Life Assurance and more
  </li>
 </ul>
</div>


Senior Machine Learning Engineer

Explore 78+ Machine learning architect in London this August. Find roles across top companies and apply now to boost your career.