ml platform engineer

Agile Robots SE

<div>
 
 
 The AI Research Division of Agile Robots
 
 is looking for an
 
 ML Platform Engineer (m/f/d)
 
 , who will build and operate the distributed training, deployment, and experimentation infrastructure that research, data, and robotics teams depend on to move models from prototype to production.
 
 
 
 
 
 
 Your Responsibilities
 
 
 <ul>
 <li>
 
 Training Infrastructure:
 
 Design and scale distributed training workflows for large models using tools such as PyTorch Distributed, DeepSpeed, and cluster schedulers like SLURM or Kubernetes.
 </li>
 <li>
 
 ML Platform:
 
 Build and maintain containerised ML environments that support reproducible experimentation and benchmarking.
 </li>
 <li>
 
 CI/CD Pipelines:
 
 Develop and maintain CI/CD pipelines for machine learning systems to enable reliable testing, training, and deployment of models.
 </li>
 <li>
 
 Lifecycle Management:
 
 Implement experiment tracking, model versioning, and reproducibility workflows using tools such as ClearML or Weights &amp; Biases.
 </li>
 <li>
 
 Observability:
 
 Set up monitoring systems such as Prometheus and Grafana to track model performance and system health and detect drift in production.
 </li>
 <li>
 
 Cross-Team Collaboration:
 
 Work with research, data, and robotics teams to connect new models to robust production systems.
 </li>
 </ul>
 
 
 
 
 
 Essential Skills
 
 
 <ul>
 <li>
 
 Background and Experience:
 
 Degree in Computer Science, Software Engineering, or a related field, with professional experience building and operating ML or software infrastructure in production.
 </li>
 <li>
 
 Distributed Training:
 
 Experience designing and operating distributed training systems on Kubernetes and Docker, using PyTorch Distributed, DeepSpeed, and schedulers such as SLURM.
 </li>
 <li>
 
 CI/CD For ML:
 
 Experience building CI/CD pipelines that support reliable model testing, training, and deployment.
 </li>
 <li>
 
 Cloud Infrastructure:
 
 Experience operating ML workloads on cloud infrastructure, preferably AWS.
 </li>
 <li>
 
 Experiment Tracking:
 
 Hands-on experience with experiment tracking and model versioning using tools such as MLflow or Weights &amp; Biases.
 </li>
 <li>
 
 Observability:
 
 Experience with monitoring and drift detection using tools such as Prometheus and Grafana.
 </li>
 <li>
 
 Software Engineering:
 
 Python and system design skills, with experience building and operating ML systems beyond the prototype stage.
 </li>
 </ul>
 
 
 
 
 
 Beneficial Skills
 
 
 <ul>
 <li>
 
 Multimodal Systems:
 
 Experience with large-scale or multimodal ML systems such as vision-language-action models.
 </li>
 <li>
 
 Infrastructure As Code:
 
 Familiarity with infrastructure-as-code tools such as Terraform.
 </li>
 <li>
 
 ML Orchestration:
 
 Experience with ML pipeline and orchestration tools.
 </li>
 <li>
 
 Distributed Compute:
 
 Exposure to high-performance or distributed compute environments.
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Dynamic high-tech company combined with financial soundness and world class investors.
 </li>
 <li>
 Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
 </li>
 <li>
 Lots of development opportunities in the context of our continued growth.
 </li>
 <li>
 Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
 </li>
 <li>
 Corporate Benefits Program that covers health, mobility and learning with 100 &euro; net per month.
 </li>
 <li>
 Modern office facilites with a rooftop terrace overlooking Munich, free drinks &amp; fruits, and regular company events contribute to a good working environment.
 </li>
 </ul>
 
 
 
 
 
 Agile Robots SE
 
 is an international high-tech company based in Munich, Germany with a production site in Kaufbeuren and more than 2300 employees worldwide. Our mission is to bridge the gap between artificial intelligence and robotics by developing systems that combine state-of-the-art force-moment-sensing and world-leading image-processing technology. This unique combination of technologies allows us to provide user-friendly and affordable robotic solutions that enable intelligent precision assembly.
 
 
 
 
 
 This is made possible by our employees, who bring out the best in each and every day with creativity and enthusiasm. Become part of this team and shape the future of robotics with us!
 
 
 We are proud of our diversity and welcome your application regardless of gender and sexual identity, nationality, ethnicity, religion, age, or disability.
 
</div>

ML Platform Engineer (m/f/d)

MetaVoice

<div>
 
 At MetaVoice, our goal is an
 
 AI for voice conversations that's as natural as talking to a person.
 
 
 
 
 
 
 Today's voice AI fails at real-world conversations. It&rsquo;s slow, turn-based like a walkie-talkie, breaks with interruptions, and doesn&rsquo;t understand emotion.
 
 
 
 
 
 Developers can't build compelling experiences and users disengage. This limits voice AI to simple receptionist tasks and basic customer support, blocking meaningful services (sales, therapy, coaching) where dialogue and emotional intelligence matter most. Scaling current tech does not work.
 
 
 
 
 
 We're building voice AI that's as natural as talking to a person. Our approach is a duplex speech-to-speech model that learns conversational behaviour directly from data.
 
 
 
 
 
 MetaVoice is founded by:
 
 <ul>
 <li>
 Sid, founding engineer at Wayve.ai ( $2.5B+ raised)
 </li>
 <li>
 Vatsal, co-created Alexa&rsquo;s first AI voice.
 </li>
 </ul>
 
 
 
 
 We&rsquo;re passionate about building products people truly love.
 
 
 
 
 
 
 The role
 
 
 
 This is a founding engineer role owning the ML data &amp; evaluation platform that model development runs on.
 
 
 
 
 
 
 Who we're looking for
 
 
 
 You&rsquo;ve worked on distributed ML infra and understand that model quality is often a data problem. You:
 
 <ul>
 <li>
 Have a track record of taking initiative and learning things quickly.
 </li>
 <li>
 Care deeply about the people using the systems you build, whether they're researchers, operators or customers
 </li>
 <li>
 Have built something yourself (startup, side project, etc) or worked in an early-stage startup
 </li>
 </ul>
 
 
 
 
 
 What you've done
 
 
 <ul>
 <li>
 Built distributed ML data pipelines to generate datasets for training and evaluation, including curation, sampling and slicing.
 </li>
 <li>
 Built and operated MLOps infrastructure to train, evaluate and serve ML models, including versioning, orchestration and observability.
 </li>
 <li>
 Built eval systems to measure model quality and catch regressions.
 </li>
 <li>
 Developed internal tools and workflows for researchers and operators to explore data and iterate fast.
 </li>
 </ul>
 
 Strong plus:
 
 <ul>
 <li>
 Designed data flywheels: automated data collection and model update loops.
 </li>
 <li>
 Designed evaluation frameworks: automated or human-in-the-loop
 </li>
 <li>
 Experience with speech, audio, or conversational datasets
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Change the world (when we succeed)
 </li>
 <li>
 Environment to do the best work of your life.
 </li>
 <li>
 Small, humble and talent dense team.
 </li>
 <li>
 Opportunity to make cutting-edge research work in real-world scenarios.
 </li>
 <li>
 Work with 100+ TBs of data and 10B+ parameter models.
 </li>
 </ul>
 
 
 
 
 
 Culture
 
 
 <ul>
 <li>
 We're an in-person team in San Francisco &amp; love working together. It helps us learn from one another and make decisions quickly.
 </li>
 <li>
 We ship fast &amp; obsess over making customers happy.
 </li>
 <li>
 We offer high autonomy, allowing everyone to do their best work.
 </li>
 </ul>
 
 
 
 
 
 Compensation &amp; Benefits
 
 
 <ul>
 <li>
 Significant equity as a founding team member.
 </li>
 <li>
 $180K-300K base.
 </li>
 <li>
 Immigration support, we are immigrants ourselves.
 </li>
 <li>
 Fully covered medical, dental, and vision insurance
 </li>
 </ul>
 
 
 
 
 
 Interview Process
 
 
 
 We move with speed, and aim to go from first interview to offer within a week.
 
 <ul>
 <li>
 
 Vibe check, 30 mins:
 
 chat with one of the founders about the mission, product and your background
 </li>
 <li>
 
 Technical Interview: 30 mins
 
 </li>
 <li>
 
 Culture interview: 30 mins
 
 </li>
 <li>
 
 Onsite co-work:
 
 Spend half a day with us. We'll build and iterate on a problem together.
 </li>
 </ul>
 
 
</div>

ML Platform Engineer (Data & Evals)

Southern Glazer’s Wine & Spirits

Job ID: 41851
 
Location: 
Dallas, TX, US, 75254 Miramar, FL, US, 33027
 
#job-location.job-location-inline { display: inline; }
 Overview
 
Employer: Southern Glazer’s Wine and Spirits LLC
 Job Title: Principal AI/ML Operations Platform Engineer
 Locations: 2300 SW 145th Avenue, Miramar, FL 33027
 14911 Quorum Drive, Dallas, TX 75254
 
Duties
 Design, build, and deploy machine learning (ML) models to derive actionable insights and solve complex problems.
 Work in the full lifecycle of ML model development from data preparation and feature engineering to model training, evaluation, and deployment.
 Apply a variety of ML algorithms, techniques, and frameworks to solve complex business challenges.
 Assemble modules into end-to-end systems, ensuring seamless integration and functionality.
 Collaborate closely with Data Scientists to facilitate highly productive experimentation, model construction, and validation, fostering a sense of teamwork and shared success.
 Apply programming skills in Python with popular deep learning and natural language processing (NLP) tools and libraries, including Scikit-learn, Pandas, PyTorch, TensorFlow, or other leading deep learning frameworks, NLTK and spaCy for natural language processing tasks.
 Contribute to the continuous improvement of ML systems by staying abreast of advancements in software engineering and ML.
 May telecommute but must reside near Miramar, Florida headquarters or Dallas, Texas office.
 Requires up to 10% domestic travel.
 Requirements
 Master’s degree (or foreign equivalent) in computer science or related field; plus 5 years of experience in job offered or software development operations and data engineering.
 Bachelor’s degree plus 7 years of experience also acceptable.
 Knowledge of programming languages (Python, R, or SQL), Terraform, Kubernetes, Unix, CI/CD tools, and AWS or Azure cloud ecosystems.
 Experience with cloud operations, DevSecOps, and deploying ML models into production environments.
 Apply
 
Apply: https://jobs.southernglazers.com/.
 
EEO Statement
 
Southern Glazer's Wine and Spirits, an Affirmative Action/EEO employer, prohibits discrimination and harassment of any type and provides equal employment opportunities to all employees and applicants for employment 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. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. SGWS complies with all federal, state and local laws concerning consideration of a qualified applicant's arrest and/or criminal conviction records. Southern Glazer's Wine and Spirits provides competitive compensation based on estimated performance level consistent with the past relevant experience, knowledge, skills, abilities and education of employees. Unless otherwise expressly stated, any pay ranges posted here are estimates from outside of Southern Glazer's Wine and Spirits and do not reflect Southern Glazer's pay bands or ranges.
 
If you have any questions or concerns about whether this posting complies/adheres with local pay transparency requirements, please contact the SGWS talent acquisition team at NationalTA@sgws.com
 
Nearest Major Market: Dallas
 Nearest Secondary Market: Fort Worth
 Job Segment: Cloud, Construction, Recruiting, Software Engineer, Computer Science, Technology, Engineering, Human Resources

Principal AI/ML Ops Platform Engineer

EssilorLuxottica

<div><div>Requisition ID: 934441 
Store #: A00152 Tech Srvcs Wholesale DAL-T 
Position: Full-Time 
Total Rewards: Benefits/Incentive Information</div> 
<div></div>
<div>
If you&rsquo;ve worn a pair of glasses, we&rsquo;ve already met.</div>
<div>
We are a global leader in the design, manufacture, and distribution of ophthalmic lenses, frames, and sunglasses. We offer our industry stakeholders in over 150 countries access to a global platform of high-quality vision care products such as the Essilor brand, with Varilux, Crizal, Eyezen, Stellest and Transitions, iconic brands that consumers love such as Ray-Ban, Oakley, Persol and Oliver Peoples, as well as a network that offers consumers high-quality vision care and best-in-class shopping experiences such as Sunglass Hut, LensCrafters, and Target Optical, and leading e-commerce platforms.</div>
<div>
Our portfolio of more than 150 renowned brands span various categories, from frames, lenses and instruments to brick and mortar and digital distribution as well as mid-range to premium segments. Our Shared Services Team, accompany and enable others within the EssilorLuxottica collective to achieve their targets. They keep people and projects running smoothly, ensuring every part of our business is provided for and well taken care of.</div>
<div>
Join our global community of over 200,000 dedicated employees around the world in driving the transformation of the eyewear and eyecare industry. Discover more by following us on LinkedIn!</div><div>
GENERAL FUNCTION
</div><div>The Data &amp; ML Engineer is a self-sufficient engineering professional responsible for designing, building, and operating scalable, secure, and reliable data and machine learning platforms primarily on Azure, with exposure to multi-cloud environments (AWS, GCP) where applicable.</div>
<div>
Expertise in programming languages such as Python or Scala, experience with data processing frameworks like Spark, and familiarity with container orchestration tools such as Kubernetes are essential for this role. Proficiency with CI/CD pipelines, DevOps, and MLOps practices is expected to ensure robust deployment and operationalization of analytics and AI solutions.</div>
<div>
This role complements the Applied Data Scientist by owning the engineering foundations required to operationalize analytics and AI solutions.</div>
<div>
MAJOR DUTIES AND RESPONSIBILITIES</div>
<div>
Managing</div>
<div>
Managing the design, development, and operation of large-scale data ingestion, transformation, and storage pipelines 
Managing ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment 
Managing platform performance, cost optimization, reliability, and availability 
Managing data security, governance, and regulatory compliance across platforms 
Managing collaboration with Applied Data Scientists to productionize models</div>
<div>
Organizing</div>
<div>
Designing and organizing ETL/ELT workflows using Azure Data Factory and orchestration tools 
Structuring Lakehouse, Azure Data Lake, and Synapse environments for scalable analytics 
Organizing data formats, schemas, and versioning (Delta, Parquet, JSON, CSV) 
Structuring reusable data pipelines and ML components to accelerate delivery 
Organizing monitoring, logging, and alerting for data and ML pipelines</div>
<div>
Leading</div>
<div>
Leading engineering best practices for scalable data and ML platformsDriving automation-first and infrastructure-as-code approaches 
Guiding solution design to ensure performance, resilience, and cost efficiency 
Leading troubleshooting and root-cause analysis for data and ML pipeline issues 
Mentoring engineers on cloud-native, big data, and MLOps practices</div>
<div>
BASIC QUALIFICATION</div>
<div>
Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field 
Proven experience as a Data Engineer, ML Engineer, or Platform Engineer 
Strong hands-on experience with Azure cloud services and big data platforms 
Proficiency in Python, SQL, Scala, and scripting languages 
Strong experience building production-grade data pipelines 
Demonstrated ability to independently own and deliver complex data and ML engineering solutions end-to-end</div>
<div>
This position is not available for visa sponsorship or transfer. Candidates must have authorization to work in the United States</div>
<div>
PREFERRED QUALIFICATIONS</div>
<div>
Master&rsquo;s degree in Computer Science, Engineering, or related discipline 
Experience with Azure Databricks, Spark, Synapse, and MLFlow 
Experience with Docker, AKS, APIs, and containerized ML workloads 
Experience with orchestration tools such as Azure Data Factory or Airflow 
 Exposure to SAP CDC and enterprise data integration 
 Experience working in agile, fast-paced, cross-functional environments</div>
<div>
TECHNICAL &amp; BEHAVIORAL SKILLS</div>
<div>
Strong engineering ownership mindset with minimal supervision 
Ability to translate analytical requirements into scalable engineering solutions 
Strong collaboration skills with data scientists and business-facing teams 
 Excellent problem-solving and troubleshooting capabilities 
 Focus on reliability, scalability, and operational excellence</div><div>
This posting is for an existing vacancy within our business. Employee pay is determined by multiple factors, including geography, experience, qualifications, skills and local minimum wage requirements. In addition, you may also be offered a competitive bonus and/or commission plan, which complements a first-class total rewards package. Benefits may include health care, retirement savings, paid time off/vacation, and various employee discounts.</div> 
<div></div>
<div>
EssilorLuxottica complies with all applicable laws related to the application and hiring process. If you would like to provide feedback regarding an active job posting, or if you are an individual with a disability who would like to request a reasonable accommodation, please call the EssilorLuxottica SpeakUp Hotline at 844-303-0229 (be sure to provide your name, job id number, and contact information so that we may follow up in a timely manner) or email HRCompliance@luxotticaretail.com.</div> 
<div></div>
<div>
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, gender, national origin, social origin, social condition, being perceived as a victim of domestic violence, sexual aggression or stalking, religion, age, disability, sexual orientation, gender identity or expression, citizenship, ancestry, veteran or military status, marital status, pregnancy (including unlawful discrimination on the basis of a legally protected pregnancy or maternity leave), genetic information or any other characteristics protected by law. Native Americans in the US receive preference in accordance with Tribal Law.</div></div>

Data & ML Engineer

Harnham

<div>
 
 
 MLOps Engineer
 
 
 
 
 Amsterdam, Netherlands (hybrid working)
 
 
 
 
 Up to 107k annually + benefits
 
 
 
 
 
 
 This is an opportunity to work on large scale, real time machine learning systems that directly impact millions of digital transactions. You will join a growing ML platform team focused on delivering robust, production ready solutions across payments and fraud, with strong ownership and visibility from day one.
 
 
 
 
 
 
 The Company
 
 
 
 They are a global technology organisation operating at the intersection of data, payments, and digital experiences. Their platform supports high volume, real time transactions for well known international businesses, focusing on performance, reliability, and innovation. With a strong engineering culture, they invest heavily in data and machine learning to drive continuous improvement. Teams are collaborative, fast paced, and committed to delivering meaningful impact.
 
 
 
 
 
 
 The Role
 
 
 
 You will focus on building and scaling MLOps capabilities within a production environment, supporting a range of machine learning use cases.
 
 
 
 
 <ul>
 <li>
 Design and build scalable systems for training, deploying, and monitoring machine learning models
 </li>
 <li>
 Support real time and batch ML workflows across critical platform services
 </li>
 <li>
 Develop and scale feature store capabilities for both online and offline use cases
 </li>
 <li>
 Improve observability and monitoring across ML systems
 </li>
 <li>
 Collaborate closely with data scientists and engineers to productionise models
 </li>
 <li>
 Take ownership of end to end delivery of ML features and systems
 </li>
 <li>
 Contribute to best practices in MLOps, CI CD, and cloud infrastructure
 </li>
 </ul>
 
 
 
 
 
 Your Skills and Experience
 
 
 <ul>
 <li>
 Strong commercial experience in MLOps or machine learning engineering
 </li>
 <li>
 High proficiency in Python for production level systems
 </li>
 <li>
 Experience deploying and maintaining machine learning models in production environments
 </li>
 <li>
 Knowledge of monitoring, observability, and system reliability
 </li>
 <li>
 Exposure to cloud platforms, ideally AWS
 </li>
 <li>
 Familiarity with ML tools and frameworks such as TensorFlow, PyTorch, Spark, or similar
 </li>
 <li>
 Experience with tools such as Databricks, SageMaker, Kubeflow, or equivalent platforms is beneficial
 </li>
 <li>
 Strong communication skills with the ability to work across technical teams
 </li>
 <li>
 A curious mindset and a practical approach to solving complex problems
 </li>
 </ul>
 
 
 
 
 
 What They Offer
 
 
 <ul>
 <li>
 Competitive salary and benefits package
 </li>
 <li>
 Hybrid working model with a collaborative office environment in Amsterdam
 </li>
 <li>
 Opportunities to work on high impact, large scale ML systems
 </li>
 <li>
 Clear progression and career development within a growing team
 </li>
 <li>
 Supportive engineering culture with strong mentorship and ownership
 </li>
 </ul>
 
 
 
 
 
 How to Apply
 
 
 
 If you are interested in this Machine Learning Ops Engineer opportunity in Amsterdam, please apply with your CV for immediate consideration.
 
</div>

Senior MLOps Engineer

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

Explore Group

<div>
 
 
 London, 4 or 5 days onsite
 
 
 
 
 Upto &pound;120,000 + meaningful equity
 
 
 
 
 
 
 
 To meet global demand, the world needs to mine as much copper in the next 25 years as in all of human history. Current methods cannot scale to this challenge. We are a venture-backed university spin-out developing frontier technology to fix this, starting with the core of every mining company: the understanding of the orebody
 
 
 
 
 
 .
 
 Using explainable AI and value-of-information analysis, our uncertainty-aware models map subsurface resources from multimodal data. This allows mining companies to make faster, better-evidenced drilling decisions, halving costs and accelerating time to productio
 
 
 
 
 
 
 n.
 
 The R
 
 
 
 oleAs our Founding Engineer, you will build and own the pipelines that move data through our system and the infrastructure that turns our models into a reliable, auditable product. You will have full ownership over how our data and ML platform architecture evolves as we sca
 
 
 
 
 
 
 le.
 
 Key Responsibili
 
 
 <ul>
 <li>
 tiesRun MLOps by building and maintaining infrastructure for scalable training and inference, frictionless ML development, and reproducible, traceable mo
 </li>
 <li>
 delsShip clean, easy-to-debug pipeline code that is highly extensible for new workf
 </li>
 <li>
 lowsAlign with product engineers to ensure seamless integration of new models into the pro
 </li>
 </ul>
 
 
 
 
 
 duct
 
 Abou
 
 
 <ul>
 <li>
 t YouMission-driven and energized by solving hard, ambiguous problems in foundational indus
 </li>
 <li>
 triesSelf-directing with a proven track record of executing projects end-to-end and prioritizing ruthl
 </li>
 <li>
 esslyExpert Python skills and deep knowledge of modern data-pipeline to
 </li>
 <li>
 olingProven experience owning production-grade ML workflows and standing up cloud infrastru
 </li>
 <li>
 ctureBonus points if you have experience with geospatial ML platforms, scientific computing stacks, or making ML reproducible in high-stakes environ
 </li>
 </ul>
 
 
 
 ments
</div>

Machine Learning Engineer

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