artificial intelligence specialist

International Swaps and Derivatives Association

<div><div>June 30, 2026
Job Title: Assistant Director, Artificial Intelligence
Reports to: Senior Director, Digital Transformation, Analytics
Location: London
</div><div>Job purpose 
This is a hands-on role. The successful candidate will architect and build production AI systems directly, while owning delivery, quality, evaluation, and partner management across the AI Solutions Lab portfolio. The role reports to the Senior Director of Digital Transformation and head of the AI Solutions Lab. 


Duties and responsibilities
<ul>
<li>Deliver the next phase of the ISDA AI Solutions Lab&rsquo;s buildout, helping move current AI initiatives from prototype/MVP stage toward robust, scalable and member-ready delivery. Architect and build the next phase of AI agents, external and internal.</li>
<li>Own the design and delivery of AI solutions that make ISDA standards and digital solutions more accessible, usable and AI-ready for members.</li>
<li>Help shape and scale the ISDA Knowledge Base and Assistant as the governed foundation for AI-enabled access to ISDA standards, taxonomies and related IP.</li>
<li>Oversee enhancement of priority AI capabilities including the CDM Coder, DRR Translator, Tracer, cross-jurisdiction analysis and AI legal opinions initiatives.</li>
<li>Help drive development and rollout of internal AI capabilities and agents aligned with the internal AI deployment roadmap.</li>
<li>Define product requirements, broader Agents orchestration, architecture direction, evaluation harnesses and quality standards and delivery priorities across the AI Solutions Lab portfolio.</li>
<li>Work closely with internal SMEs across CDM, DRR, legal, IT and product teams to ensure solutions are accurate, grounded and useful in real workflows.</li>
<li>Reach out to members for pulse checks and convert member and stakeholder feedback into roadmap decisions, product refinements and delivery choices to maximize adoption.</li>
<li>Help define practical connectivity and delivery models, including MCP servers and packaged AI Skills, so members can consume ISDA AI capabilities safely within their own environments.</li>
<li>Contribute to broader ISDA AI strategy development, including alignment between external member-facing AI solutions and internal AI deployment priorities.</li>
<li>Lead AI quality, guardrails and governance across the Lab&rsquo;s solutions, including evaluation harnesses, groundedness and traceability checks, observability and tracing, confidence frameworks, security and safe use boundaries, both internally and externally.</li>
<li>Own cost aware design of AI workloads, balancing performance and reliability against inference and infrastructure spend.</li>
<li>Manage relevant external partners and specialist vendors, ensuring work is aligned to ISDA&rsquo;s priorities, timelines, architecture and ownership model.</li>
<li>Support the Senior Director including for executive and board reporting by articulating progress, key risks, delivery needs and strategic value in a clear and concise way.</li>
<li>Help build a durable internal AI capability for ISDA that protects ISDA IP, accelerates adoption of ISDA standards and reinforces ISDA&rsquo;s strategic position in the market.</li></ul> 


Relevant Skills / Abilities
<ul>
<li>Strong senior-level experience (at least five years) leading the design and delivery of AI-enabled products or platforms from prototype through controlled rollout and production, with a demonstrable track record of shipping production AI systems that serve real users.</li>
<li>Hands-on engineering ability in Python (and ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly.</li>
<li>Deep understanding of LLMs, retrieval-augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding-model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM-as-judge, groundedness and faithfulness metrics, tracing), and model risk controls.</li>
<li>Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions, auditability and data protection including private retrieval architectures and ensuring proprietary data is not exposed to external model providers</li>
<li>Hands-on AWS experience (Bedrock, Neptune, OpenSearch, Lambda) is very important. Strong engineers able to ramp quickly will also be considered. Cost-aware design of inference and infrastructure spend is expected.</li>
<li>Proven ability to translate complex domain knowledge into usable AI products, ideally in financial markets, regulatory technology, legal tech, standards or data-intensive environments; or a demonstrated ability to ramp quickly on a complex domain.</li>
<li>Strong product and solution architecture skills, with the ability to define use cases, prioritize roadmap items and align technical delivery with strategic business outcomes.</li>
<li>Experience overseeing external vendors, technology partners and proof-of-concept work, while retaining internal control of direction, quality and IP.</li>
<li>Ability to work closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements.</li>
<li>Strong grasp of structured data, taxonomies, ontology-style data models and mappings across complex standards or schemas.</li>
<li>Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user populations.</li>
<li>Strong judgment on AI risks, including hallucination, groundedness, security, explainability, confidence scoring and safe deployment boundaries.</li>
<li>Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline, or equivalent practical experience, is desirable.</li>
<li>Excellent communication skills, including the ability to understand member issues, to work across the organization and influence and align stakeholders, and to brief senior management and explain technical issues in concise business language.</li>
<li>Demonstrated ability to operate in a lean, hands-on environment, balancing strategy, execution and stakeholder engagement.</li></ul></div></div>

Assistant Director, Artificial Intelligence, London

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As AI moves from experimentation to enterprise-wide adoption, doing it responsibly has become a commercial necessity, not just an ethical one. We are looking for a Responsible AI Specialist to ensure the solutions we design and the advice we give to clients are trustworthy, compliant, and fair by design. This is a role for someone who can translate principles (fairness, transparency, accountability) into practical frameworks that engineering teams and clients can actually apply.
You will be a connective figure across the practice: advising delivery teams on ethical and regulatory risk, contributing to client governance conversations, and helping shape the standards by which we build. You do not need to be a deep technical engineer, but you must understand how AI systems work, where they fail, and what good governance looks like in practice, particularly as regulation such as the EU AI Act reshapes expectations.
This is a growing area of strategic importance, offering significant scope to define our approach and to become a recognised voice in responsible AI.
Required skills &amp; experience:<ul><li>
Define and implement Responsible AI frameworks, policies, and practical guidelines across the practice.</li><li>
Advise project teams on ethical AI design, risk identification, and mitigation throughout the delivery lifecycle.</li><li>
Conduct AI risk and impact assessments, and embed fairness, transparency, and accountability into solutions.</li><li>
Contribute to client conversations on AI governance, risk, and regulatory readiness.</li><li>
Monitor evolving regulation (EU AI Act, ICO guidance, emerging standards) and translate it into actionable guidance.</li><li>
Support internal capability building, raising awareness and competence in responsible AI across teams.</li><li>
Partner with architects and data scientists to operationalise governance &mdash; model documentation, evaluation, and guardrails.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 3 years in AI ethics, governance, policy, risk, compliance, or a closely related regulatory field.</li><li>
Sound understanding of AI concepts, risks, and failure modes (deep technical implementation not required).</li><li>
Working knowledge of relevant regulation and standards, including the EU AI Act.</li><li>
Strong stakeholder communication skills, able to engage both technical teams and senior business audiences.</li><li>
Ability to turn principles into pragmatic, usable frameworks and processes.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting or advisory roles.</li><li>
Familiarity with assurance frameworks (ISO/IEC 42001, NIST AI RMF).</li><li>
Background in data protection, privacy, or model risk management.</li><li>
Exposure to fairness, bias, and explainability tooling.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
Responsible AI is central to how we earn client trust and differentiate our practice. You will have the rare chance to shape this capability from an influential position, combining ethics, regulation, and real delivery in work that genuinely matters. As adoption and scrutiny grow, so will your impact and your profile.</div>

Responsible AI Specialist (Governance, Ethics & Compliance)

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.
Required skills &amp; experience:<ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</div>

AI Engineer (LLMs, Agents & Applied Data Science)

Accenture

<div>YOU ARE
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.
THE WORK<ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul>
PREFERRED QUALIFICATION<ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div>

AI/ML Computational Science Manager

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul> 
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

JPMorganChase

<div>JOB DESCRIPTION 
 
 
The Chief Data &amp; Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As an Applied AI ML Senior Associate in Machine Learning Center of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including time series analysis, reinforcement learning, causal inference, and natural language processing. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Machine Learning and Econometrics with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.
Job responsibilities
<ul><li>Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community</li>
<li>Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as time-series analysis and modelling, constrained optimization and prediction for large systems, prescriptive analytics, and decision-making in dynamical systems</li>
<li>Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production</li>
<li>Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business</li>
</ul>Required qualifications, capabilities, and skills
<ul><li>PhD in a quantitative discipline, e.g. Econometrics, Finance/Accounting, Mathematics, Computer Science, Operations Research</li>
<li>Ability to conduct literature research in unfamiliar fields</li>
<li>Hands-on experience and solid understanding of machine learning and deep learning methods</li>
<li>Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)</li>
<li>Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals</li>
<li>Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.</li>
<li>Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments</li>
<li>Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems</li>
</ul>Preferred qualifications, capabilities, and skills
<ul><li>Strong background in Mathematics and Statistics and familiarity with the financial services industries;</li>
<li>Solid knowledge in financial reports analysis; understand relationships among items in Balance Sheet, Income Statement, and Cashflow statement</li>
<li>Ability to develop and debug production-quality code and solid experience in writing unit tests, integration tests, and regression tests;</li>
<li>Published research in areas of Machine Learning/Deep Learning/Reinforcement Learning OR Finance/Accounting at a major conference or journal</li>
</ul>#MLCOE_jobs
ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Applied AI ML Senior Associate - Machine Learning Center of Excellence - Time Series Reinforcement Learning

Bloomberg

<div>
 Location
 
 
 London
 
 
 Business Area
 
 
 Engineering and CTO
 
 
 Ref #
 
 
 10049302
 
 
 
 Description &amp; Requirements
 
 
 
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 
 
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 
 
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 
 
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 
 
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 
 
 
 Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
 
 
 
 <ul>
 <li>
 Architect, build, and diagnose multi-tenant AI platform systems
 </li>
 <li>
 Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
 </li>
 <li>
 Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
 </li>
 <li>
 Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
 </li>
 <li>
 Design CI/CD automation frameworks that incorporate regulatory requirements
 </li>
 <li>
 Develop cloud-native deployment patterns for AI systems across environments
 </li>
 <li>
 Troubleshoot and debug user issues
 </li>
 <li>
 Provide operational and user-facing documentation
 
 
 </li>
 </ul>
 
 We are looking for a Senior ML Platform Engineer with:
 
 
 
 <ul>
 <li>
 Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
 </li>
 <li>
 Experience designing cloud-native, distributed platforms
 </li>
 <li>
 Strong knowledge of Kubernetes, Argo, and container orchestration technologies
 </li>
 <li>
 Previous experience with modern CI/CD tools and GitOps workflows
 </li>
 <li>
 Familiarity with implementing automation for model development lifecycles
 </li>
 <li>
 A proactive mentality and ability to collaborate with peers, stakeholders, and management
 </li>
 <li>
 A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
 </li>
 <li>
 An understanding of Computer Science fundamentals such as data structures and algorithms
 
 
 </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 
 
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 
 
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>

Senior ML Platform Engineer - Artificial Intelligence

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