senior machine learning engineer

HOMETRACK

<div>Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.
At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs.
Responsibilities:<ul><li>
Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.</li><li>
Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.</li><li>
Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.</li><li>
Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.</li></ul>
Requirements:<ul><li>
Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.</li><li>
Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.</li><li>
Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.</li><li>
Have worked with a cloud service, such as AWS.</li><li>
Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).</li><li>
Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.</li><li>
Comfortable working with Docker and containerised applications.</li><li>
Experience leveraging AI native engineering tooling.</li><li>
Passion for building products that meet customer needs and business objectives.</li><li>
Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.</li></ul> 

Benefits 
<ul><li>
Everyday Flex - greater flexibility over where and when you work</li><li>
25 days annual leave + extra days for years of service</li><li>
Day off for your birthday, house move, good deed day, and digital detox day</li><li>
Cycle to work and electric car schemes
</li><li>Free Calm App membership
</li><li>Enhanced Paternity Leave
</li><li>Fertility Treatment Financial Support
</li><li>Group Income Protection and private medical insurance</li><li>
Gym on-site in London &ndash; or membership in regional offices</li><li>
7.5% pension contribution by the company</li><li>
Discretionary annual bonus up to 10% of base salary</li><li>
Talent referral bonus up to &pound;5K</li></ul></div>

Senior Machine Learning Engineer

<div>
 Ben jij een Senior Machine Learning Engineer met interesse in het bouwen van Generative AI-oplossingen? Dan biedt deze rol bij KPN jou de kans om jouw AI-engineeringvaardigheden in te zetten binnen een AI-expertiseteam van Data Scientists en Machine Learning Engineers. In ons team werken we samen aan het verkennen, ontwikkelen en toepassen van de nieuwste (Gen)AI-technologie&euml;n. Je komt terecht in een jong, dynamisch team binnen het AI Excellence Center in Amsterdam, waar hybride werken, samenwerking en groeimogelijkheden centraal staan. Klaar om jouw carri&egrave;re naar een hoger niveau te tillen?
 
 
 Jouw rol als Senior Machine Learning Engineer
 
 
 In deze rol ben jij de drijvende kracht achter het ontwikkelen van nieuwe technologie&euml;n tot bouwstenen waarmee de hele organisatie GenAI-usecases kan realiseren. Je gebruikt geavanceerde software en tools om ervoor te zorgen dat deze oplossingen niet alleen werken, maar ook schaalbaar, betrouwbaar en continu beschikbaar zijn.
 
 
 Jouw dagelijkse werkzaamheden omvatten:
 
 
 <ul>
 <li>
 Ontwikkelen en onderhouden van production grade GenAI-oplossingen
 </li>
 <li>
 Prioriteiten bepalen en invloed uitoefenen op de roadmap van het GenAI Lab
 </li>
 <li>
 Operationaliseren en integreren van GenAI-technologie in bedrijfsprocessen, IT en dataplatformen
 </li>
 <li>
 Continu samenwerken met teamleden, domeinexperts en business stakeholders om de meest effectieve oplossingen te realiseren
 </li>
 <li>
 Begeleiden van junior teamleden en bijdragen aan AI Excellence
 
 
 </li>
 </ul>
 Dit is je team
 
 
 Je sluit je aan bij het jonge, enthousiaste Data Science Lab-team binnen het AI Excellence Center, bestaande uit meer dan 30 hoogopgeleide en energieke collega&rsquo;s.
 
 
 Als onderdeel van de AI-community werk je nauw samen met diverse specialisten, waaronder business stakeholders, domeinexperts, data engineers, software engineers, ML engineers, wiskundigen en data scientists.
 
 
 We hebben een hechte en groeiende AI-community van ongeveer 100 mensen uit verschillende teams en afdelingen. Elke maand organiseren we een VrijMiBo, een kennisuitwisseling en leuke activiteiten zoals padel, klimmen of pubquizzen.
 
 
 Wat breng
 
 
 jij ons?
 
 
 Je bent leergierig en flexibel, zowel technisch als persoonlijk. Je bent analytisch sterk en hebt een groot verantwoordelijkheidsgevoel. Je vindt het leuk om zowel technische als niet-technische collega&rsquo;s te betrekken bij je werk.
 
 
 Om succesvol te zijn in deze rol, breng je mee:
 
 
 <ul>
 <li>
 Minimaal 5 jaar ervaring als AI/ML Engineer of vergelijkbaar
 </li>
 <li>
 Een masterdiploma met een technische component, zoals Computer Science of Software Engineering
 </li>
 <li>
 Aantoonbare ervaring met het bouwen van production grade GenAI-applicaties (zoals RAG, Agentic AI, etc.)
 </li>
 <li>
 Ervaring met Python
 </li>
 <li>
 Ervaring met Azure en Infrastructure-as-Code
 </li>
 <li>
 Ervaring met ML-libraries, REST API&rsquo;s, microservices (Docker, Kubernetes, etc.)
 </li>
 <li>
 Uitstekende kennis van software-engineeringmethodologie&euml;n en best practices, waaronder coding standards, code reviews, versiebeheer, CI/CD, testen en security
 
 
 </li>
 </ul>
 Wat krijg je
 
 
 van ons?
 
 
 Natuurlijk hebben we als werkgever jou ook veel te bieden. Dit krijg je van ons:
 
 
 <ul>
 <li>
 Een bruto maandsalaris van minimaal &euro; 5.190 ,- en maximaal &euro; 7.803 ,- afhankelijk van je werkervaring, op basis van 40 uur exclusief 8% vakantiegeld
 </li>
 <li>
 Vaste 13e maand, een deel krijg je maandelijks uitbetaald en een deel in januari van het volgende jaar. &Oacute;f je zet het in voor een FLEX &amp; BOOST doel naar keuze! Klik hier om er meer over te lezen
 </li>
 <li>
 Jaarlijks een individuele en collectieve verhoging conform onze CAO
 </li>
 <li>
 &euro; 1500 per jaar aan inzetbaarheidsbudget dat je naar eigen inzicht mag gebruiken voor bijvoorbeeld trainingen, coaching en cursussen
 </li>
 <li>
 Flexibele vrije dagen: onze collega&rsquo;s mogen zelf (in samenspraak met de manager) bepalen hoe zij met verlof omgaan
 </li>
 <li>
 Een goede werk-priv&eacute; balans
 </li>
 <li>
 Thuiswerkshop om je werkplek thuis optimaal in te kunnen richten, uiteraard met een mobiele telefoon &amp; laptop
 </li>
 <li>
 50% korting op onze producten en diensten, zodat je voordelig kunt internetten, bellen &eacute;n streamen
 </li>
 <li>
 Goede reiskostenvergoeding: je krijgt je OV kosten volledig vergoed of &euro; 0,23 per kilometer als je met de auto reist. Kom je liever op de fiets? Dan kun je aanspraak maken op onze fietsvergoeding &euro; 0,40 per kilometer
 </li>
 <li>
 Mogelijkheid tot het aanschaffen van een leasefiets waar KPN maandelijks aan meebetaalt (bij onbepaalde tijd contract): Van stadsfiets tot e-bike en van racefiets tot speed-pedelec; jij kiest waar je op fietst
 </li>
 <li>
 Uitstekende pensioenvoorwaarden: een totale inleg van 23% van je pensioengevende salaris waarvan KPN 16% inlegt en jij 7%
 
 
 </li>
 </ul>
 Ons geloof in technologie is groot. Dit wordt n&oacute;g krachtiger samen met menselijk contact, daarom ontmoeten we je graag!
 
 
 Wil je meer weten? Neem contact op met onze recruiter Szilvia Haraszti via szilvia.haraszti@kpn.com
</div>

Unifonic

<div>
 
 Job Description
 
 
 
 Proudly voted a Great Place to Work&reg;, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
 
 
 We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we&rsquo;re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
 
 
 
 Meet the team!
 
 
 
 Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic&rsquo;s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.
 
 
 As a Senior Machine Learning (AI) Engineer, you will be responsible for designing, developing, and deploying advanced machine learning solutions across various domains, including NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies.
 
 
 
 Help Us Shape The Future Of Communication By
 
 
 
 <ul>
 <li>
 Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
 </li>
 <li>
 Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content.
 </li>
 <li>
 Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
 </li>
 <li>
 Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search).
 </li>
 <li>
 Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches.
 </li>
 <li>
 Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products.
 </li>
 <li>
 Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
 </li>
 <li>
 Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI).
 </li>
 <li>
 Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode.
 </li>
 <li>
 Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
 </li>
 <li>
 Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
 </li>
 <li>
 Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture.
 </li>
 <li>
 Assisting in the project documentation and demos.
 
 
 </li>
 </ul>
 
 Job Requirements
 
 
 
 
 What you'll bring:
 
 
 
 <ul>
 <li>
 Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies (e.g., BM25, dense retrieval, hybrid approaches) and knowledge graph integration.
 </li>
 <li>
 Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
 </li>
 <li>
 Deep expertise in various NLP techniques and models, including but not limited to:
 
 
 </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 
 
 Large Language Models (LLMs) and their fine-tuning/adaptation
 
 
 Vector embeddings and similarity search
 
 
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 
 
 <ul>
 <li>
 Hands-on 3-5 years of relevant work experience as a Machine Learning Engineer.
 </li>
 <li>
 Hands-on 3+ years of experience with Python.
 </li>
 <li>
 Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
 </li>
 <li>
 End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
 </li>
 <li>
 Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modeling
 </li>
 <li>
 Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
 </li>
 <li>
 Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.
 </li>
 <li>
 Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
 </li>
 <li>
 Basic knowledge of Kubernetes and Docker is nice to have.
 </li>
 <li>
 Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
 </li>
 <li>
 Experience with the Hugging Face libraries (i.e. transformers).
 </li>
 <li>
 Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
 </li>
 <li>
 Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
 </li>
 <li>
 Familiar with Agile methodologies i.e. scrum and kanban.
 </li>
 <li>
 Ability to develop high-level architecture and low-level design, End-to-end for a specific project.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is a plus.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques is nice to have.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is nice to have.
 </li>
 <li>
 General knowledge of Data warehouse tools e.g. Vertica is a plus.
 </li>
 <li>
 A Bachelor&rsquo;s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Software, etc).
 </li>
 <li>
 Excellent communication and collaboration skills.
 </li>
 <li>
 Good level of spoken and written Arabic and English.
 
 
 </li>
 </ul>
 
 As a Unifone you will receive a range of benefits:
 
 
 
 <ul>
 <li>
 Competitive salary and bonus.
 </li>
 <li>
 Unifonic share scheme (we are all owners!).
 </li>
 <li>
 30 holiday days after the first anniversary.
 </li>
 <li>
 Your Birthday off!
 </li>
 <li>
 Spend up to 25 days per year working from anywhere in the world!
 </li>
 <li>
 Paid leave for new parents.
 </li>
 </ul>
</div>

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Lobster Data GmbH

<div><h4 class="jobSectionHeader">Position Overview:</h4>
This is a vacancy for a hybrid or on-site role at our HQ in Tutzing (South of Munich) or Amsterdam. We encourage applications from all qualified candidates, regardless of gender identity. 
 
As we continue to expand and evolve our Supply-Chain-focused Data Integration Platform, we're looking for a Senior Machine Learning / Artificial Intelligence Engineer (m/f/x) to join our Product &amp; Engineering team. 
 
In this role, you will help design and implement AI/ML &amp; GenAI solutions that enhance our data integration offerings and push our platform capabilities forward. Our mission is to connect people, data and intelligence (human &amp; artificial) to optimise processes across the supply chain, always choosing the right tool for the right challenge. 
 
Ready to make an impact?<h4 class="jobSectionHeader">
You&rsquo;ll get to take ownership of:</h4><ul><li>
Developing Pathfinder, a multi-agent AI system built on protocol-driven, microservice-oriented architecture &ndash; where specialised agents are dynamically orchestrated to assist users in navigating the complexities of data integration, automating routine tasks and proactively solving problems to make them significantly more productive.</li><li>
Defining and implementing scalable microservices that drive data mapping, transformation, and intelligent integration.</li><li>
Developing and maintaining RESTful and/or GraphQL APIs to ensure seamless communication between services and systems.</li><li>
Creating and optimising event-driven data pipelines to enable real-time processing, automation, and decision-making across our products.</li><li>
Evaluating, selecting, and implementing the best-fit tools and technologies to solve complex engineering and data challenges effectively.</li><li>
Collaborating directly with key customers and internal stakeholders to validate solution performance and ensure product impact and usability.</li></ul><h4 class="jobSectionHeader"> 
We&rsquo;d love to meet someone with:</h4><ul><li>
5+ years of engineering experience focused on Machine Learning, AI, and Data Science/Data Engineering.</li><li>
Hands-on production GenAI experience with LLMs, NLP, and agentic AI &ndash; including multi-agent orchestration, tool integration via MCP, and inter-agent communication patterns such as A2A.</li><li>
Hands-on production ML/AI experience with PyTorch and MLOps frameworks.</li><li>
Strong skills in Python development, including building microservices and working with event-driven architectures.</li><li>
Proficiency in designing and consuming RESTful or GraphQL APIs.</li><li>
Experience with AWS or Azure ML services (e.g., SageMaker, Bedrock, Azure ML) and cloud-native development.</li><li>
Experience with CI/CD (GitHub Enterprise) and Infrastructure-as-Code (Terraform, Pulumi).</li><li>
Strong communication skills in English.</li></ul><h4 class="jobSectionHeader">
You can look forward to:</h4><ul><li>
Opportunity to work flexibly from home</li><li>
Modern offices in Germanyandthe Netherlands</li><li>
A personal Learning &amp; Development budget</li><li>
Up to30 daysof remote work per year from any EU country</li><li>
Company Pension plan</li><li>
30 vacation days a year</li><li>
2additionalpaid days off on Christmas Eve and New Year's Eve</li><li>
Location-specific benefits packages (your recruiter will be happy to provide more details during your first chat)</li><li>
Company-sponsored business travel</li></ul>
 
For this role, we are open to working with specialists based in Germany and the Netherlands. Whether you prefer working on-site at our offices in Tutzing or Amsterdam, or remotely from a location within one of these countries, we&rsquo;re happy to accommodate your preferred working style. 
 
If you&rsquo;re excited about this role but don&rsquo;t meet every qualification, we encourage you to apply!
 
 
Lobster is an equal opportunity employer. We are committed to fostering a diverse and inclusive environment where empathy and respect guide our interactions.<h4 class="jobSectionHeader">
About us</h4><div>
Lobster is a pioneering no-code software company that enables organisations to unlock the full potential of their data. Its comprehensive Data Platform allows companies to integrate, manage, and automate data efficiently, while its Data Network facilitates secure and seamless data exchange between partners and systems. From connectivity to consumable Data Products, Lobster&rsquo;s solutions empower businesses across industries to stay agile and competitive. With a presence in DACH, the UK, France, Scandinavia, and the Benelux region, Lobster serves over 2,000 customers globally.</div></div>

Onsera Health

<div>
 
 The Challenge
 
 
 Cardiometabolic conditions will impact 80-90% of people throughout their lifetimes, representing the leading cause of death globally and an important risk factor for neurodegenerative diseases and cancer. Sustainably addressing these diseases requires breakthrough therapeutics, AI/ML innovation, and transformative business models that translate clinical outcomes into economic value.
 
 
 The Opportunity
 
 
 This is an opportunity to build the ML and AI foundations of Onsera Health's breakthrough healthcare platform. Backed by Population Health Partners (PHP)&mdash;the proven venture platform behind Metsera and Corsera Health&mdash;we're building the future of population health management.
 
 
 
 As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems.
 
 Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards.
 
 
 Responsibilities
 
 <ul>
 <li>
 
 Design and implement Onsera's agentic AI platform
 
 &ndash; architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability
 </li>
 <li>
 
 Define MLOps protocols for agentic systems
 
 &ndash; environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms
 </li>
 <li>
 
 Bridge data science and platform engineering
 
 &ndash; translate experimentation needs into GCP infrastructure, scalable compute patterns, and reproducible development environments
 </li>
 <li>
 
 Productionize data science code
 
 &ndash; convert research-grade notebooks into tested, modular, production-grade Python services, batch and streaming pipelines, and scheduled workflows
 </li>
 <li>
 
 Build production-grade data pipelines
 
 &ndash; develop idempotent, observable, and cost-efficient pipelines using BigQuery, Airflow, Google Workflows, and Cloud Run
 </li>
 <li>
 
 Implement CI/CD for ML workloads
 
 &ndash; automated validation, monitoring, rollback strategies, and model lifecycle management
 </li>
 <li>
 
 Establish reliability and governance
 
 &ndash; logging, metrics, tracing, data quality checks, and auditability for model decisions, data lineage, and agent actions
 </li>
 </ul>
 
 What We Offer
 
 <ul>
 <li>
 Mission-driven work addressing critical public health and healthcare economics challenges
 </li>
 <li>
 Ground-floor opportunity to build the ML/AI infrastructure for a breakthrough healthcare platform
 </li>
 <li>
 Partnership with a world-class team of industry leaders, innovators, technologists, bioscientists, and clinicians from PHP and beyond
 </li>
 <li>
 A fast-paced, dynamic, and highly collaborative work environment
 </li>
 <li>
 Competitive salary and benefits package, including participation in our equity program
 </li>
 </ul>
 
 
 
 
 Minimum Qualifications
 
 <ul>
 <li>
 5+ years of experience in machine learning engineering, data engineering, or a related field
 </li>
 <li>
 Strong Python engineering skills with production-quality, typed, and tested code
 </li>
 <li>
 Track record productionizing ML models in batch and/or real-time environments
 </li>
 <li>
 Hands-on experience with analytical data warehouses (BigQuery or equivalent) and workflow orchestration (Airflow or similar)
 </li>
 <li>
 Experience deploying ML systems on GCP, including Cloud Run, GCS, and IAM
 </li>
 <li>
 Infrastructure-as-Code experience (Terraform or equivalent)
 </li>
 <li>
 Experience with feature engineering, model lifecycle management, and ML evaluation
 </li>
 <li>
 Demonstrated ability to collaborate across Data Science, Product, and Platform teams
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience with LLMs, agent frameworks, or AI orchestration systems in production
 </li>
 <li>
 Familiarity with prompt management, tool calling, evaluation, and AI safety patterns
 </li>
 <li>
 Healthcare or regulated-industry experience, including familiarity with HIPAA or SOC-2 compliance
 </li>
 <li>
 Experience with claims data, EHR-derived datasets, or real-world evidence
 </li>
 <li>
 Strong written and verbal communication skills with technical and non-technical stakeholders
 </li>
 </ul>
 
 About Onsera Health
 
 
 We are an early-stage health AI company revolutionizing cardiometabolic care and population health economics connected to weight loss. Our unique position within the PHP ecosystem provides:
 
 <ul>
 <li>
 
 Venture track record:
 
 A proven track record of success in building biotech and healthcare companies
 </li>
 <li>
 
 Deep capital:
 
 Funding and resourcing to support deep tech and scientific R&amp;D&mdash;and to drive growth
 </li>
 <li>
 
 Strategic guidance:
 
 Direct access to industry pioneers (including founders of The Medicines Company and Metsera), healthcare experts (including leaders in virtual care, former FDA commissioners), strategists (McKinsey/QuantumBlack alumni), and world-class scientific talent
 </li>
 <li>
 
 Expert network:
 
 Established connections across pharma, payers, and providers
 </li>
 <li>
 
 Startup agility:
 
 Ownership in the venture, founder mentality, and ground-floor impact
 </li>
 </ul>
 
 About PHP
 
 
 Population Health Partners (PHP) is a premier investment firm established in 2020, aimed at transforming health outcomes for large populations. With offices in New York and London, PHP combines financial resources with industry-leading capabilities and technology. The firm's incubation portfolio includes Metsera and Corsera Health.
 
 
 
 Leadership:
 
 Led by industry veterans including Clive Meanwell (The Medicines Company), Chris Cox (The Medicines Company), and Whit Bernard (Metsera), bringing decades of founder experience and operational excellence in biopharma and healthcare, and Roy Berggren, 30+ year McKinsey Healthcare leader.
 
</div>

<div><div><div>Job ID: R0048311</div>
</div><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><div><div>We believe in better. And we make it happen.
Better content. Better products. And better careers.
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.
We turn big ideas into the products, content and services millions of people love.
And we do it all right here at Sky.
What you'll do
 
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.
<ul><li>Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.</li>
<li>Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.</li>
<li>Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.</li>
<li>Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.</li>
<li>Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.</li>
<li>Research &amp; Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.</li> 
</ul> 
What you'll bring
<ul><li>Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
</li><li>Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .</li>
<li>Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).</li>
<li>Experience with high-volume data processing and real-time streaming architectures.</li>
<li>Strong understanding of recommendation system design and personalisation algorithms.</li>
<li>Familiarity with Generative AI and its applications in production settings.</li>
<li>Exceptional communication and analytical problem-solving skills.</li>
<li>Proven successful experience in mentoring less experienced engineers to improve their technical skills</li>
</ul>A Typical Day at the Office
When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) caf&eacute;s or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand-up. After that, you&rsquo;ll join your team and pick the first task to get cracking on.
At lunchtime, you&rsquo;ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup &ndash; whatever suits you. Once you&rsquo;re back, you&rsquo;ll carry on working with your team on your current feature.
Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.
Global OTT Technology
Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world&rsquo;s best entertainment, news and sport.
The rewards
There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here&rsquo;s a taster:
<ul><li>Sky Q, for the TV you love all in one place</li>
<li>The magic of Sky Glass at an exclusive rate</li>
<li>A generous pension package</li>
<li>Private healthcare</li>
<li>Discounted mobile and broadband</li>
<li>A wide range of Sky VIP rewards and experiences</li>
</ul>Inclusion &amp; how you'll work
We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.
We&rsquo;ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You&rsquo;ll find out more about what hybrid working looks like for your role later on in the recruitment process.
Your office space
Osterley
Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.
On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.
We'd love to hear from you
Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next.
But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.
If you believe in better, we&rsquo;ll back you all the way.
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.</div></div></div>

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