ml platform engineer

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

Worldpay

<div>Ready to take your career global?
Make your mark at one of the biggest names in payments.
We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators&mdash;including ML research engineers, product managers, and platform engineers&mdash;to deliver scalable, reliable, and low-latency ML solutions.
In addition to technical expertise, this job requires strong collaboration skills.
What you&rsquo;ll own
Feature Development &amp; Delivery:<ul><li>
Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.</li></ul>
Technical Ownership and Stewardship:<ul><li>
Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.</li><li>
End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.</li></ul>
Contribute to ML platform:<ul><li>
Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.</li></ul>
Operational Excellence:<ul><li>
Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.</li><li>
Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.</li></ul>
Continuous Improvement:<ul><li>
Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.</li></ul>
Release Management:<ul><li>
Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.</li></ul>
Leadership:<ul><li>
Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.</li><li>
Mentor and coach other engineers, supporting their professional growth.</li><li>
Foster a culture of collaboration, continuous improvement, and knowledge sharing.</li></ul>
Act Like an Owner:<ul><li>
Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.</li><li>
Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.</li></ul>
What you&rsquo;ll bring<ul><li>
5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience</li><li>
Proven expertise with ML model deployment, API design, and integration into production environments</li><li>
Strong Python programming and relevant ML/data libraries</li><li>
Experience with containerization, orchestration, and AWS cloud services</li><li>
Building and operating CI/CD pipelines</li><li>
Monitoring, troubleshooting, and optimizing production ML systems</li><li>
Pre-release testing and release management</li><li>
Demonstrated ability to work independently, navigate ambiguity, and deliver results</li><li>
Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams</li><li>
Experience with OpenAPI, FastAPI, or similar</li></ul>
It&rsquo;s a bonus if you have<ul><li>
Experience with MLFlow, model versioning, and storage</li><li>
Familiarity with Databricks or similar platforms</li><li>
Experience supporting high-volume, real-time data products</li><li>
Automated testing and validation frameworks</li><li>
Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB</li><li>
Experience with Terraform Cloud</li><li>
Experience in large companies, mature engineering teams, and/or highly regulated industries</li><li>
AI-assisted coding experience (e.g. GitHub Copilot)</li></ul>
Why Join Us?<ul><li>
Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company&rsquo;s strategy. Your work will directly influence the reliability, scalability, and evolution of critical production systems.</li><li>
Autonomy: Take end-to-end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.</li><li>
Collaboration: Join a cross-functional, high-performing team where your expertise is valued and your contributions make a real difference.</li></ul>
About the team
Our inclusive and global teams win together every day. We&rsquo;re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.
What makes a Globalpayer?
Globalpayers think like a client, act like an owner, and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.
#LI-AB1</div>

Senior ML Software Engineer

Few&Far

<div>
 
 🚨
 
 Senior Data Engineer | Outside IR35 Contract | Up to &pound;525/day | London (1 day onsite)
 
 🚨
 
 
 
 
 
 I'm working with a growing business that's looking for a Senior Data Engineer to join on an initial 6-12 month contract.
 
 
 
 
 
 💰
 
 Up to &pound;525 per day
 
 
 
 📍
 
 London - 1 day per week onsite
 
 
 
 📄
 
 Outside IR35
 
 
 
 ⚡
 
 1-stage interview process
 
 
 
 
 
 
 This is a fantastic opportunity to play a key role in modernising a cloud-based data platform while helping to future-proof the company's infrastructure and mentoring junior engineers as they continue to develop.
 
 
 
 
 
 You'll be working on:
 
 
 ✅ Modernising data lake &amp; data warehouse architecture
 
 
 ✅ Designing, building and optimising ETL/ELT pipelines
 
 
 ✅ Deploying and supporting production ML systems, including forecasting models, LLM-powered and agentic workflows
 
 
 ✅ Enhancing an AWS-native data platform (S3, Redshift, RDS, Athena, SageMaker &amp; Lambda)
 
 
 ✅ Writing high-performance SQL and production-quality Python
 
 
 ✅ Improving platform reliability, monitoring and CI/CD
 
 
 ✅ Collaborating with stakeholders to deliver scalable data solutions
 
 
 ✅ Mentoring junior engineers through code reviews and best practices
 
 
 
 
 
 
 Tech Stack:
 
 
 
 ☁️ AWS
 
 
 🐍 Python
 
 
 🗄️ SQL
 
 
 🔄 Airflow (AWS)
 
 
 📊 Looker (nice to have)
 
 
 
 
 
 I'm keen to speak with Data Engineers who have:
 
 
 ✔️ Strong experience building production-grade data pipelines
 
 
 ✔️ Advanced SQL and Python skills
 
 
 ✔️ Experience deploying and supporting ML models in production
 
 
 ✔️ AWS cloud experience and a solid understanding of DevOps/platform engineering
 
 
 
 
 
 If you're available soon or know someone who could be a great fit, please apply below or share this job post!
 
</div>

Senior Data Engineer

Wise Australia Investments

<div><div><div>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money. 
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money. 
For everyone, everywhere.
. 
Job Description 
About the role:
Wise moves billions across borders every year. Behind every transaction is a decision: is this safe? Our ML systems make that call - at scale, in real time, across every market we operate in.
Our Risk ML team is building the next generation of financial crime detection at Wise - investing in modern architectures like deep learning, graph neural networks, and foundation models to detect increasingly sophisticated fraud and money laundering patterns. We're looking for a Staff Applied ML Engineer to lead this evolution: defining the architecture strategy, shipping production neural models, and building the blueprint that scales across FinCrime domains.
This is a greenfield opportunity - you'll be setting the direction for how Wise applies modern ML to financial crime risk, with strong investment and engagement from senior leadership.
How we work:
Risk ML sits within Wise's FinCrime organisation, owning the full ML and AI foundation for financial crime detection. We're scaling into three dedicated pillars - Feature Platform, Learning Loop and Risk Modelling. You'll sit in Risk Modelling, working alongside data scientists, platform engineers, product and domain experts.
We operate with high autonomy and low hierarchy. You'll own problems end-to-end - from research and architecture decisions through to production deployment and impact measurement. We value engineers who shape direction, not just execute tickets.
What will you be working on?<ul><li>
Designing and shipping ML and deep learning models for financial crime detection - sequence-based, graph-based, attention-based - serving real-time decisions at Wise's scale</li><li>
Defining the architecture strategy for how Wise applies modern ML to risk - which model families, which serving patterns, which training paradigms</li><li>
Building the reusable end-to-end pipeline pattern - from experimentation through training to production deployment - that future models follow</li><li>
Evaluating and prototyping foundation model and embedding approaches for transaction representation across FinCrime domains</li><li>
Partnering with Data Science on model evaluation, experimentation design and causal measurement in domains where clean A/B testing isn't always possible</li><li>
Mentoring engineers and data scientists on modern ML fundamentals, production best practices, and architectural decision-making</li></ul>
What do you need?<ul><li>
Production experience shipping deep learning models at scale - systems serving real traffic under latency constraints</li><li>
Ability to make architecture-level decisions independently - model selection, training infrastructure, serving strategy - and explain the reasoning and tradeoffs</li><li>
Experience designing ML systems with hard latency and throughput requirements, including optimisation decisions (quantization, pre-computed embeddings, batching strategies)</li><li>
Strong fundamentals in deep learning: gradient dynamics, attention mechanisms, graph message-passing, sequence modelling</li><li>
Track record of influencing technical strategy across teams - you don't just build, you shape direction</li><li>
Python, PyTorch (or equivalent), distributed training, ML pipeline orchestration</li></ul>
Nice to Have:<ul><li>
Experience in FinCrime, fraud detection, AML, or regulated financial services</li><li>
Experience with graph-based methods (GNNs, entity resolution, link analysis) in production</li><li>
Foundation model fine-tuning or LLM evaluation experience</li><li>
Experience establishing modern ML practices in organisations scaling their ML capabilities</li></ul>
Interested? Find out more:<ul><li>
How we work &ndash; a practical guide</li><li>
DEI @ Wise</li><li>
Wise Tech Stack (2025 update)</li><li>
See what it's like to work at Wise London!</li><li>
Our Engineering career map</li><li>
Wise Engineering &ndash; https://medium.com/wise-engineering</li></ul>
What do we offer:<ul><li>
Starting salary: &pound;145,000 - &pound;182,000 + RSUs</li><li>
Wise Benefits</li></ul>
#LI-AB3 #LI-Hybrid 
Additional Information<div></div> 
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences. 
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on </div></div><div><div><div><div>Instagram</div></div></div></div></div><div></div>

Staff Applied ML Engineer - Financial Crime

Muzz

<div>
 
 
 London, UK - Hybrid (Tue, Wed &amp; Thur in Office)
 
 
 
 
 &pound;80,000 - &pound;90,000 + equity
 
 
 
 
 
 
 We&rsquo;re looking for a smart and ambitious data scientist, with real entrepreneurial flair to join our team and understand our members and all the metrics that matter. Love numbers and love being commercial? This role presents an opportunity to mold the future of the data science team, explore new ideas and new technologies.
 
 
 
 
 
 Muzz is the world&rsquo;s largest Muslim dating and marriage app. We&rsquo;ve got over 15 million members and have helped more than 800,000 couples get married. We&rsquo;re on our way to become the first $1 billion Muslim tech brand - but we need your help!
 
 
 
 
 
 
 Day to day
 
 
 <ul>
 <li>
 You'll be joining a dynamic data science team whose goal is to grow the company and optimize our products as we expand into new markets around the world
 </li>
 <li>
 You'll be understanding our user behaviour on the platform with a view to generating actionable insights in terms of both product and marketing
 </li>
 <li>
 You'll work closely with our product, engineering and growth teams
 </li>
 <li>
 You'll be a proactive self-starter, driving innovation with a product focus
 </li>
 <li>
 You&rsquo;ll be diving into a range of data to solve our highest impact and complex challenges
 </li>
 <li>
 You'll own and evolve the production ML systems behind our personalization and recommendations serving millions of users
 </li>
 <li>
 You'll use AI tools as a core part of how you work and help set how the wider team gets the most out of them
 </li>
 <li>
 You'll raise the bar for the team - mentoring analysts and data scientists, and helping shape our technical standards and roadmap
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 At least 5 years of experience in a Data Scientist or Machine Learning Engineer role
 </li>
 <li>
 Strong Python and SQL knowledge
 </li>
 <li>
 Strong grounding in the statistical methods behind personalization and recommendations models - e.g. embeddings, ranking, collaborative filtering
 </li>
 <li>
 Excellent written and verbal communication skills and presenting to non-technical audiences
 </li>
 <li>
 Commercial mindset with the ability to harness customer insights to optimise our marketing and products
 </li>
 <li>
 Ability to work collaboratively in cross-functional teams
 </li>
 <li>
 Passionate about solving complex and challenging data problems
 </li>
 <li>
 Experience in designing and conducting A/B experiments
 </li>
 <li>
 A proven track record of developing and owning production ML pipelines - including data processing, deployment, monitoring, retraining
 </li>
 <li>
 Demonstrated end-to-end ownership of significant ML projects - from framing the problem to shipping it, and through the messy realities of live performance, edge cases and iteration once real users hit it
 </li>
 </ul>
 
 
 
 
 
 Nice to have
 
 
 <ul>
 <li>
 Hands-on experience with recommender systems, with real-time or near-real-time updates and serving
 </li>
 <li>
 Experience in consumer-facing mobile-first products
 </li>
 <li>
 Experience with GCP platform - BigQuery/VertexAI
 </li>
 </ul>
 
 
 
</div>

Senior Data Scientist

Intact Insurance UK

<div>
 
 APPLY NOW!
 
 
 
 Intact Insurance is the new name for RSA in the UK, Ireland, and across Europe. It&rsquo;s a new name and a new way to do business. Backed by global expertise and a commitment to service that feels different, we&rsquo;re focused on making insurance simpler, faster, and more responsive.
 
 
 
 Shape The Future
 
 
 
 We&rsquo;re leading a transformation in insurance helping people, businesses and society prosper in good times and be resilient in bad times. When you join us, you&rsquo;re not just taking a job, you&rsquo;re stepping into a career where you can make a real difference.
 
 
 
 Grow With Us
 
 
 
 We&rsquo;re customer-driven, community-focused, and committed to helping our people grow. Whether you&rsquo;re early in your journey or bringing years of experience, we&rsquo;ll support you with the tools, flexibility, and opportunities to thrive.
 
 
 
 Win As a Team
 
 
 
 We&rsquo;re looking for a Machine Learning Engineer to help build and run production-ready ML systems that make a real impact across the business. You&rsquo;ll work closely with Data Scientists and engineering teams, shaping the ML roadmap, developing scalable solutions, and driving innovation while growing your career.
 
 
 
 You&rsquo;ll Make An Impact By
 
 
 
 <ul>
 <li>
 Build and automate ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
 </li>
 <li>
 Productionise Data Science models, converting notebooks into modular, tested, production-ready code.
 </li>
 <li>
 Deploy models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
 </li>
 <li>
 Implement monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
 </li>
 <li>
 Collaborate with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
 </li>
 <li>
 Maintain engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.
 
 
 </li>
 </ul>
 
 Your Skills And Experience
 
 
 
 <ul>
 <li>
 Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
 </li>
 <li>
 Proficient in Python, PySpark, and SQL, following production coding best practices.
 </li>
 <li>
 Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
 </li>
 <li>
 Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
 </li>
 <li>
 Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.
 
 
 </li>
 </ul>
 
 Why You&rsquo;ll Love It Here
 
 
 
 Being part of our team means you&rsquo;ll have the support and freedom to bring your best self to work each day. As a permanent member, here&rsquo;s what you can look forward to
 
 
 <ul>
 <li>
 Annual discretionary bonus
 </li>
 <li>
 Up to 11% pension contributions
 </li>
 <li>
 Hybrid working + flexible hours
 </li>
 <li>
 25 days annual leave + bank holidays + buy/sell options
 </li>
 <li>
 Health &amp; wellbeing + virtual GP
 </li>
 <li>
 Career development and mentoring
 </li>
 <li>
 Inclusive culture + employee networks
 </li>
 <li>
 Share investment options
 
 
 </li>
 </ul>
 
 Our DEI Commitment
 
 
 
 We celebrate individuality and believe our differences make us stronger. We&rsquo;re proud to foster a culture where everyone feels respected, valued, and empowered to thrive.
 
 
 As an Equal Opportunity and Disability Confident Employer, we ensure fair consideration for all applicants and offer interviews to all disabled candidates who meet the essential criteria.
 
 
 We understand that everyone&rsquo;s circumstances are different and are happy to explore flexible working options such as reduced hours or job shares to support work&ndash;life balance.
 
 
 If you meet the core criteria but not every requirement, we&rsquo;d still love to hear from you. Let&rsquo;s explore how this role could support your next career step. If you need adjustments during the recruitment process, just let us know we&rsquo;re here to support you.
 
 
</div>

Machine Learning Engineer

Bluefish AI

<div>About the Position

As a Staff AI Engineer, you&rsquo;ll serve as a technical leader for our LLM-powered products at the forefront of marketing and advertising technologies. You&rsquo;ll own critical architectural decisions, set quality bars, and lead multi‑team initiatives that drive measurable outcomes.

As our Staff AI Engineer, you will lead the vision and execution of our data platform and LLM-powered products. You&rsquo;ll own critical architectural decisions across data pipelines, model integration, model deployment and evals: turning high-level product and business requirements into robust, scalable data products that drive measurable outcomes for our Fortune 500 customers. This role spans data backend and ML engineering: from the reliability and cost efficiency of our pipelines to the outcome and performance of LLM-enabled features. You&rsquo;ll raise the bar for data literacy across the department, craft and collaboration.

You&rsquo;ll be accountable for the health, cost, and evolution of key data product and data platforms, partnering closely with full-stack engineers, product, design, and devops to deliver outcomes our customers can trust.

This role presents an exciting opportunity to shape the future of AI-driven technologies and make meaningful contributions to real-world applications.

The role is linked with our location in London, but we are flexible about hybrid or remote work in The United Kingdom.

What You&rsquo;ll Be Doing
<ul>
<li>Lead end-to-end architecture for data platforms and pipelines: scraping, data extraction, transformation, storage, serving, and ML/LLM integration, balancing performance, reliability, security, and cost.</li>
<li>Incrementally scale pipelines and systems: design safe rollout plans and north star data-quality metrics to handle customer and traffic growth without impacting production.</li>
<li>Translate business goals into actionable data products: assess high-level requirements, carve clear problem spaces, draft crisp RFCs, and sequence work into deliverable projects for the team.</li>
<li>Establish and enforce engineering standards: testing strategy, evals, observability, data contracts, and security practices across services. Think through short-term and long-term goals to come up with fast go-to-market products, while planning ahead for productization.</li>
<li>Up‑level the org: lead architecture reviews, codify patterns, mentor Senior Engineers, and multiply impact through documentation, code reviews, and pairing.</li>
<li>Startup‑ready: flexible, comfortable with ambiguity and constant change; proactive about process, documentation, and reliability without over‑engineering.</li>
<li>Lead the collaboration and define how AI engineers work cross-functionally with software engineers, devops, product managers and designers, to conceptualize and shape innovative and impactful solutions. Provide mentorship to junior team members and cultivate a culture of collaboration and innovation.</li>
<li>Ship meaningful experiments: prototype data/ML capabilities, evaluate feasibility and ROI, and make pragmatic calls on productionalizing with an eye on operating costs and risk.</li>
</ul>
Qualifications
<ul>
<li>8+ years building and operating production data systems, including leading cross-cutting architectural changes, and deploying LLMs in real‑world scenarios at scale.</li>
<li>Deep experience Python and modern service architectures; strong system design and data modeling fundamentals.</li>
<li>Extensive experience with training and deploying machine learning models, particularly within the NLP/LLM domain. Proficiency in Python. Familiarity with infrastructure as code, CI/CD, and cloud infrastructure.</li>
<li>Fluency in operational maturity: SLOs, on‑call/incident practices, and observability.</li>
<li>Strong analytical and problem-solving abilities, with a bias towards action and outcomes. Experience with data preprocessing, feature engineering, and model evaluation techniques.</li>
<li>Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Demonstrated leadership experience, with the ability to guide and inspire a team.</li></ul> 


About Bluefish:

Bluefish believes that AI represents the next major chapter of the internet &ndash; and that consumers will increasingly use AI to consume information and media online. On this new AI internet, brands will need new tools and technologies to tell their stories to consumers online &ndash; and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage AI brand safety and engage consumers with thoughtful and personalized AI marketing experiences.

The Bluefish team is a tight-knit group of mar-tech industry veterans who previously helped build foundational ad-tech platforms now owned by Meta and Microsoft. Bluefish, the leading AI marketing platform for the Fortune 500, recently announced a $43 million Series B growth financing co-led by Threshold Ventures and NEA with participation from multiple enterprise investors including Amex Ventures, TIAA Ventures, Salesforce Ventures, and continued participation from Bloomberg Beta. We are a globally distributed team, with business operations based in New York City and engineering based in Europe and New York.

Why Bluefish &amp; Our Values:
<ul>
<li>Unique opportunity to join on the ground floor of a fast-moving startup building at the center of AI</li>
<li>Tackle challenging and abstract problems while disrupting the $300BN legacy mar-tech industry</li>
<li>Join an experienced high-performing team where you will have immediate ownership and impact</li>
<li>Experience a true meritocracy with significant career growth upside as the business scales</li>
</ul>
Our Values:
<ul>
<li>Demonstrated grit and resourcefulness - you find creative solutions, adapt quickly, and aren&rsquo;t afraid to roll up your sleeves in a fast-paced, evolving environment.</li>
<li>Thoughtful and strategic thinker with the ability to anticipate needs, ask the right questions, and deliver insights that truly drive value.</li>
<li>Proven ability to collaborate across functions and roles, fostering open communication and shared ownership of outcomes.</li>
<li>Commitment to craftsmanship - you take pride in delivering high-quality work, paying attention to the small details while keeping the big picture in mind.</li>
<li>Self-starter with a proactive mindset and a strong sense of accountability - able to drive projects forward independently while staying aligned with team goals.</li>
<li>Comfortable navigating ambiguity and learning new tools, processes, or technologies to get the job done.</li></ul></div>

Staff AI Engineer

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