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

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>

<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>

Senior Machine Learning Engineer (Recommendation)

Picnic Technologies

<div>
 In a nutshell
 
 
 As a Machine Learning Engineer at Picnic, you will design and deploy intelligent systems to solve our company&rsquo;s biggest challenges. Beyond building models, you will productionize them with strong monitoring and seamless integration into operational systems. You will collaborate closely with stakeholders to ensure the right problems are solved and that solutions deliver real-world impact.
 
 
 All using high quality data. Our data is registered, logged, and consistent, enabling you to focus on building and improving models rather than cleaning data. This role combines the skills of a consultant, software engineer, and applied mathematician.
 
 
 Tricks of the trade
 
 
 You will definitely:
 
 
 <ul>
 <li>
 Identify and execute improvement possibilities together with other ML Engineers and (product) analysts
 </li>
 <li>
 Collaborate on your project from inception to production, to continuous improvement
 </li>
 <li>
 Develop tools and enhancements for our cloud-based Machine Learning platform
 
 
 
 </li>
 </ul>
 You could work on various projects and fields, such as:
 
 
 <ul>
 <li>
 Demand forecasting: delivery, article, trip volumes, used Picnic-wide
 </li>
 <li>
 Fraud detection: helping us keep troublemakers out of our store
 </li>
 <li>
 Recommendation systems: generating useful in-app grocery suggestions
 </li>
 <li>
 Search and ranking: helping our customers find exactly what they need
 </li>
 <li>
 Predicting delivery drop-off times: making sure we&rsquo;re on-time at every customer&rsquo;s door
 </li>
 <li>
 Vision: ensuring quality control and smooth operations within our warehouses
 
 
 
 </li>
 </ul>
 Check out some of our previous machine learning projects here: https://blog.picnic.nl/tagged/machine-learning
 
 
 We&rsquo;re looking for
 
 
 <ul>
 <li>
 Master&rsquo;s degree or higher in AI, Computer Science, Mathematics, or a related field
 </li>
 <li>
 5+ years of experience in data science or applied machine learning
 </li>
 <li>
 Excellent communication skills, you can clearly explain complex ideas in non-technical terms and enjoy working closely with business stakeholders to solve problems together
 </li>
 <li>
 Experienced in designing, deploying, and maintaining production ML systems, with solid software engineering and ML principles
 </li>
 <li>
 Strong Python and SQL skills
 </li>
 <li>
 Able to define the long-term vision and technical architecture for ML solutions within your domain
 </li>
 <li>
 Experience with Docker, Kubernetes, and CI is a plus
 
 
 
 </li>
 </ul>
 Picnic Perks
 
 
 
 🫱🏼&zwj;🫲🏾 Teamwork makes the dream work
 
 
 
 With more than 80 nationalities across 3 countries, you&rsquo;ll be part of a diverse company with plenty of cool stuff to get involved with, from board game evenings to after-work drinks to our company ski trip and more!
 
 
 
 💡 Make a difference
 
 
 
 You&rsquo;ll work in an awesome startup environment with the freedom to drive your own projects and create a visible impact. Our fully electric vehicles and sustainable business model mean you&rsquo;ll also be contributing to making the world a better place!
 
 
 
 🥗 Fresh Lunch, coffee, and snacks
 
 
 
 Our offices are equipped with fully-fledged coffee bars and a kitchen and chefs. They prepare delicious fresh and warm lunches every day so you can keep your energy up.
 
 
 
 🚲 Health insurance discount &amp; bike plan
 
 
 
 We have a partnership with CZ (a health insurance provider). Picnic employees get a discount on CZ insurance packages between 5% and 15%. Furthermore, through our partnership with Lease a Bike, you can rent-to-own a new (e)bike at a discounted rate
 
 
 
 🌎 Relocation
 
 
 
 If you&rsquo;re moving from another country to join Picnic we make it as smooth as possible for you. We&rsquo;ll cover your flight costs for you and your partner and kids, your first month's rent and moving costs (up to &euro;2000), and help you with the 30% tax ruling setup and application.
 
 
 
 📆 All the rest
 
 
 
 At Picnic you get 25 holidays, we cover your travel expenses and offer a pension plan. And your phone and laptop are on us, as well.
</div>

PROXIMIE

<div>Proximie is on a mission to improve healthcare by transforming the world&rsquo;s operating rooms into connected ecosystems of people, devices, and data.<div>
Our Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events &ndash; improving quality of data outputs. The result: ORs are optimised like never before &ndash; with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.
Once practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce &ndash; improving outcomes and saving lives.
Proximie was commercialised in 2019 and is available in over 500 facilities globally.
Check out our Founder and CEO Nadine&rsquo;s Origins Story here: https://www.proximie.com/about-us/
Position Overview
As Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decisions making, using your deep technical expertise and real-world experience you will be instrumental in developing and deploying machine learning solutions that improve clinical outcomes, drive productivity and support Proximie&rsquo;s continuing evolution into the unrivalled champion of the intelligent operating room.
You will work with multi-modal data (audio, vision, and language) to curate, consolidate, and augment retrospective and prospective datasets that fuel the development of advanced machine learning solutions. You&rsquo;ll harness the power of Proximie&rsquo;s deep data lakes and apply cutting-edge generative techniques to solve real-world challenges for Proximie&rsquo;s customers. You&rsquo;ll also lead the development of intelligent systems that can automatically detect and capture key events in the operating room, designing robust solutions that work across diverse and unpredictable data distributions, tackling challenges like identifying rare events buried in hours of surgical video.
This role demands creativity, precision, and a deep understanding of real-world machine learning at scale. If you&rsquo;re excited by complex problems with life-changing impact and want to build tech that operates in the most critical environments, we&rsquo;d love to hear from you.
Responsibilities<ul><li>
Collaborate with product, engineering and commercial teams to develop and deploy AI models for real world application in hospitals all over the world.</li><li>
Design, train and validate machine learning mono and multi-modal models using state of the art approaches.</li><li>
Develop models and derived tools robust to the heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design.</li><li>
Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance.</li><li>
Development within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie&rsquo;s data lakes.</li><li>
Document solutions and contribute to internal knowledge sharing and capability building.</li></ul><div>
Requirements<ul><li>
PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred.</li><li>
Minimum of 4 years&rsquo; hands-on experience in industry, developing and deploying AI solutions which solve real-world problems.</li><li>
Expertise in developing, training and fine-tuning machine learning and multi-modal models. Experience in training models with data originating from heterogeneous distributions is highly desirable.</li><li>
Deep knowledge of a variety of traditional machine learning, deep learning and generative AI methods for both supervised, self-supervised and unsupervised learning with an emphasis on vision.</li><li>
Proficiency with deep learning frameworks such as TensorFlow/PyTorch.</li><li>
Proficiency with Python and strong software development background.</li><li>
Knowledge and experience with AWS is highly desirable.</li><li>
Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.</li><li>
Ability to communicate complex technical concepts clearly to non-technical stakeholders.</li></ul>
Why Work for Proximie?<ul><li>
You will be encouraged to grow in your role, take ownership and gain responsibilities. Proximie&rsquo;s values are Ownership, Deliver Results, Build Trust and Go Beyond.</li><li>
Generous annual leave.</li><li>
Two &ldquo;well-being&rdquo; days per year plus the day off for your birthday.</li><li>
&ldquo;Summer Fridays&rdquo; &ndash; early office closing on Fridays during summer months.</li><li>
Annual bonus programme &ndash; based on individual contribution.</li><li>
To support your professional growth, all permanent employees will have access to an annual stipend of &pound;1,000 to assist with personal development activities.</li><li>
Flexible working hours - we trust our people to manage their time and to focus on wider results.</li><li>
A flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.</li><li>
Proximie is a truly global company with teams across the UK, Europe, United States and the Middle East with that you will have opportunities to see the world.</li></ul>
Proximie is an equal opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under the law.</div></div></div>

Roblox

<div>San Mateo, CA, United StatesEarly CareerID: 6400</div>
 <div><div><div>Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences&ndash; all created by our global community of developers and creators.
At Roblox, we&rsquo;re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We&rsquo;re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you&rsquo;ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.</div>
Team
<ul>
<li>Creator Services Machine Intelligence Team: The Machine Intelligence team is building an NPC system that can (1) play any Roblox game and (2) perform real-time inference efficiently enough to support deployment to all Roblox players.
</li><li>ML Platform Team: The Foundation AI Group is on a mission to establish Roblox as the standard for 3D foundational models (3DFMs), democratizing creation by making it simple for anyone to generate high-quality, immersive 3D experiences using AI. The AI Platform team is a foundational part of this vision, supporting hundreds of ML use cases and billions of inferences daily across Discovery, Safety, Engine, and more. We are seeking exceptional PhD new graduates to drive innovation across three critical areas: AI Platform, Distributed Inference Systems.</li>
</ul>
What You Will Do

As a Senior Machine Learning Engineer, you will be a key contributor to building the cutting-edge systems that power AI at Roblox.
Creator Services Machine Intelligence Team
<ul>
<li>Develop Scale Data Pipelines: Design, build and maintain robust data pipelines to collect complex 3D game states and real-time player actions across the platform.</li>
<li>Train Novel Architectures: Solve the feature extraction across games for NPC model in a general and scalable way and drive model training speed for novel, sophisticated deep learning architectures.</li>
<li>Optimize Real-Time Inference: Engineer high-performance model inference solutions to support the seamless deployment of 10s to 100s of autonomous NPCs in real-time environments.</li>
</ul>
ML Platform Team

Track 1: AI Platform Projects
<ul>
<li>Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.</li>
<li>Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.</li>
<li>Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.</li>
</ul>
Track 2: Distributed Inference &amp; Systems Optimization
<ul>
<li>Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.</li>
<li>Optimize our inference engine to serve millions of QPS at low latency.</li>
<li>Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.</li>
</ul>
You Have
<ul>
<li>Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox&rsquo;s research areas.</li>
<li>Built end-to-end ML pipelines and managed model inference and deployment.</li>
<li>Experience with novel datasets, and building real-world agentic applications.</li>
<li>Scaled high-performance, high-availability architectures.</li>
<li>Handled infrastructure using Kubernetes and major cloud providers (AWS, Azure, or GCP).</li>
</ul><div><div><div>
For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.</div><div>
Annual Salary Range</div><div>
$196,750&mdash;$243,290 USD</div></div></div><div>
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.

For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.</div></div></div>

[2026] Senior Machine Learning Engineer (Systems), Embodied AI/NPCs, ML Platform - PhD Early Career

Agoda

<div>
 
 About Agoda
 
 
 
 At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
 
 
 Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
 
 
 No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you&rsquo;re ready to begin your best journey and help build travel for the world, join us.
 
 
 
 Get to Know Our Team
 
 
 
 The Engineering department oversees all Agoda&rsquo;s ML and software related requirements. Our goal is to enable and increase Agoda&rsquo;s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company&rsquo;s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.
 
 
 
 Why Agoda Engineering Team (ML role)?
 
 
 
 Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API&rsquo;s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.
 
 
 
 In this Role, you will get to:
 
 
 
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 Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes. Build, administer and scale ML processing pipelines.
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 Be comfortable navigating the following technology stack: Python3, Scala Spark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
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 Should be able to understand internals of ML models such as LightGBM, Random Forest, CNN, Regression models, etc
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 Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
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 Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
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 We believe in end-to-end ownership; this role will involve taking and building systems that enable us to deliver ML models to production at a scale.
 
 
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 </ul>
 
 What You&rsquo;ll need to Succeed:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science /information systems/engineering/related field 6+ years of experience in software engineering with a minimum of 4+ years in ML
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 Expert in SQL, Python3, and JVM based programming language &ndash; ie, Java or Scala
 </li>
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 Expert in software design/design patterns, functional programming and object-oriented programming.
 </li>
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 Analytical problem-solving capabilities &amp; experience. A strong engineering driven mindset will be required to succeed in this role.
 
 
 </li>
 </ul>
 
 It&rsquo;s great if you have:
 
 
 
 <ul>
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 Good understanding of Hadoop ecosystems and Big Data architecture and techologies
 </li>
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 Experience working with Open-source products
 </li>
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 Experience with Scala development
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 Working in an agile environment using test driven methodologies
 </li>
 <li>
 Systems administration skills in Linux
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Hybrid Working Model
 </li>
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 WFH Set Up Allowance
 </li>
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 30 Days of Remote Working from anywhere globally every year
 </li>
 <li>
 Employee discount for accommodation globally
 </li>
 <li>
 Global team of 90+ nationalities
 </li>
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 40+ offices and 25+ countries
 </li>
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 Annual CSR / Volunteer Time off
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 Benevity Subscription for employee donations
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 Volunteering opportunities globally
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 Free Headspace subscription
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 Free Odilo &amp; Udemy subscriptions
 </li>
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 Access to Employee Assistance Program (third party for personal and workplace support)
 </li>
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 Enhanced Parental Leave
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 Life, TPD &amp; Accident Insurance
 
 
 </li>
 </ul>
 #telaviv #jerusalem #IT #ENG #4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #shanghai #beijing #shenzhen #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #hongkong #budapest #jakarta #bali #dublin #telaviv #milan #rome #venice #florence #naples #turin #palermo #bologna #tokyo #osaka #kualalumpur #malta #amsterdam #oslo #manila #warsaw #krakow #doha #alrayyan #riyadh #jeddah #mecca #medina #singapore #seoul #barcelona #madrid #stockholm #zurich #taipei #tainan #taichung #kaohsiung #bangkok #Phuket #istanbul #london #manchester #edinburgh #hcmc #hanoi #lodz #wroclaw #poznan #katowice #rio #salvador #newdelhi #bangalore #bandung #yokohama #nagoya #okinawa #fukuoka #jerusalem #IT #4 #newdelhi #Pune #Hyderabad #Bangalore #Mumbai #Bengaluru #Chennai #Kolkata #Lucknow #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #shanghai #beijing #shenzhen #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #hongkong #budapest #jakarta #bali #dublin #telaviv #milan #rome #tokyo #osaka #kualalumpur #amsterdam #oslo #manila #warsaw #krakow #bucharest #moscow #saintpetersburg #capetown #johannesburg #seoul #barcelona #madrid #stockholm #zurich #taipei #bangkok #Phuket #istanbul #london #manchester #edinburgh #kiev #hcmc #hanoi #wroclaw #poznan #katowice #rio #salvador #IT #4 #5
 
 
 Please review our Hiring Process Guidelines before your interview &mdash; click here to learn how interviewing at Agoda works.
 
 
 
 Discover More About Working At Agoda
 
 
 
 <ul>
 <li>
 Agoda Careers https://careersatagoda.com
 </li>
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 Facebook https://www.facebook.com/agodacareers/
 </li>
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 LinkedIn https://www.linkedin.com/company/agoda
 </li>
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 YouTube https://www.youtube.com/agodalife
 
 
 </li>
 </ul>
 
 Equal Opportunity Employer
 
 
 
 At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person&rsquo;s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
 
 
 We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
 
 
 
 Disclaimer
 
 
 
 We do not accept any terms or conditions, nor do we recognize any agency&rsquo;s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.
 
 
</div>

Senior/Staff Machine Learning Engineer - Bidding (Bangkok based, relocation provided)

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