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Job Title: Front-End Software Engineer – React & Python

Location: Eindhoven

Type: Full-Time

About the Company:

A leading global media and marketing organization, the company is focused on leveraging data, AI, and technology to deliver intelligent, scalable solutions for clients worldwide. The company combines deep industry expertise with advanced technology to transform how brands connect with audiences.

Role Overview:

The organisation are seeking a talented Front-End Software Engineer to join its internal technology team. The role will focus on building and maintaining modern, scalable web applications using React for the front-end and Python for backend services. The engineer will work closely with cross-functional teams to deliver high-quality, production-ready software that supports critical business operations.

Key Responsibilities:

• Design, develop, and maintain responsive, user-friendly web applications using React.
• Collaborate with backend engineers working in Python to integrate APIs and services.
• Ensure code quality through testing, code reviews, and adherence to best practices.
• Optimize applications for performance, scalability, and maintainability.
• Work closely with product managers, designers, and stakeholders to translate requirements into technical solutions.
• Contribute to improving internal development processes, CI/CD pipelines, and deployment workflows.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Strong experience with React, modern JavaScript (ES6+), and front-end frameworks.
• Experience with Python and building backend services or APIs.
• Familiarity with version control systems (e.g., Git) and CI/CD workflows.
• Understanding of web performance, accessibility, and responsive design principles.
• Strong problem-solving skills and ability to work collaboratively in a fast-paced environment.

Preferred:

• Experience with cloud platforms (AWS, GCP, Azure).
• Familiarity with TypeScript, Node.js, or full-stack development.
• Previous experience in media, advertising, or marketing technology is a plus.

Why Join:

• Work at the intersection of media, data, and technology within a global organization.
• Opportunity to develop production-grade software that impacts core business operations.
• Collaborative, innovative, and inclusive culture with opportunities for continuous learning and growth

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Senior Software Engineer, Machine Learning

$170,000-$215,000 + bonus & benefits

Remote – U.S., UK, or Canada

About the Company

We’re a remote-first product and engineering organization building AI-powered tools that help teams work better together, explore ideas, and make more informed decisions. Our focus is on augmenting human creativity and collaboration, not replacing it, by embedding intelligent systems directly into everyday workflows.

We operate at the intersection of applied machine learning, thoughtful product design, and scalable systems, with a strong emphasis on shipping production AI that delivers real value. The team is globally distributed, highly collaborative, and driven by ownership and impact.

About the Role

We’re hiring a Senior Machine Learning Engineer to design and ship production AI systems that support collaboration and decision-making at scale. This role blends applied ML, product development, and scalable infrastructure, with meaningful ownership over user-facing features.

What You’ll Do

• Build and deploy generative AI and RAG systems used in real workflows

• Develop data pipelines for training, evaluation, and continuous improvement

• Create human-in-the-loop processes to improve model quality

• Partner with product and engineering on user-facing AI features

• Collaborate on training, inference, monitoring, and deployment

What We’re Looking For

• 5+ years building and shipping production ML systems

• Strong Python with PyTorch or TensorFlow

• Experience with LLMs, embeddings, retrieval, or ranking systems

• Comfortable owning systems end-to-end and mentoring others

Nice to Have

• MLOps or ML infrastructure experience

• Experience working on creative or collaboration-focused ML products

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About the Role

We are looking for a Data Analytics Engineer who sits at the intersection of data engineering and analytics. In this role, you will transform raw, messy data from vehicles, APIs, and operational systems into clean, reliable datasets that are trusted and widely used-from engineering teams to executive leadership.

You will own data pipelines end to end and build dashboards that surface insights, track performance, and help teams quickly identify issues.

What You’ll Do

• Build and maintain ETL pipelines that ingest data from diverse internal systems into a centralized analytics warehouse
• Work with unique and high-volume datasets, including vehicle telemetry, sensor-derived signals, logistics data, and system test results
• Write efficient, well-structured SQL to model and prepare data for analysis and reporting
• Design, build, and maintain dashboards (e.g., Grafana or similar) used to monitor system performance and operational health
• Partner closely with engineering, operations, and leadership teams to understand data needs and deliver actionable datasets
• Explore internal AI- and LLM-based tools to automate analysis and uncover new insights

What You’ll Need

• Strong hands-on experience with Python and data libraries such as pandas, Polars, or similar
• Advanced SQL skills, including complex joins, window functions, and query optimization
• Proven experience building and operating ETL pipelines using modern data tooling
• Experience with BI and visualization tools (e.g., Grafana, Tableau, Looker)
• Familiarity with workflow orchestration tools such as Airflow, Dagster, or Prefect
• High-level understanding of LLMs and interest in applying them to data and analytics workflows
• Strong ownership mindset and commitment to data quality and reliability

Nice to Have

• Experience with ClickHouse or other analytical databases (e.g., Snowflake, BigQuery, Redshift)
• Background working with vehicle, sensor, or logistics data
• Prior experience in autonomous systems, robotics, or other data-intensive hardware-driven domains

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What You’ll Do

• Own and evolve the metrics platform, including schemas, storage layouts optimized for high-volume writes and fast analytical reads, and clear versioning strategies
• Build and maintain a framework for writing and running metrics, including interfaces, examples, local execution, and CI compatibility checks
• Design and implement testing systems for metrics and pipelines, including unit, contract, and regression tests using synthetic and sampled data
• Operate compute and storage systems in production, with responsibility for monitoring, debugging, stability, and cost awareness
• Partner with metric authors and stakeholders across development, analytics, and QA to plan changes and roll them out safely

What You’ll Need

• Strong experience using Python in production, including asynchronous programming (e.g., asyncio, aiohttp, FastAPI)
• Advanced SQL skills, including complex joins, window functions, CTEs, and query optimization through execution plan analysis
• Solid understanding of data structures and algorithms, with the ability to make informed performance trade-offs
• Experience with databases, especially PostgreSQL (required); experience with ClickHouse is a strong plus
• Understanding of OLTP vs. OLAP trade-offs and how schema and storage decisions affect performance
• Experience with workflow orchestration tools such as Airflow (used today), Prefect, Argo, or Dagster
• Familiarity with data libraries and validation frameworks (NumPy, pandas, Pydantic, or equivalents)
• Experience building web services (FastAPI, Flask, Django, or similar)
• Comfort working with containers and orchestration tools like Docker and Kubernetes
• Experience working with large-scale datasets and data-intensive systems

Nice to Have

• Ability to read and make small changes in C++ code
• Experience building ML-adjacent metrics or evaluation infrastructure
• Familiarity with Parquet and object storage layout/partitioning strategies
• Experience with Kafka or task queues
• Exposure to basic observability practices (logging, metrics, tracing)

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Engineering Manager, Enterprise Security

Fully Remote – USA

$200,000 – $250,000

The Opportunity

My client is expanding their Enterprise Security product line and are looking for a technical leader to build and scale the engineering team behind it. This group develops the security capabilities that enterprise IT leaders rely on to approve, deploy, and trust our platform.

You’ll lead the development of high-impact features such as data loss prevention, audit logging, SIEM integrations, encryption controls, and data governance capabilities. These products are directly tied to large enterprise deals and long-term revenue growth.

This role combines hands-on technical leadership with team building and product ownership. You’ll shape the roadmap, define success metrics, and ensure we deliver enterprise-grade security features that meet the highest standards of reliability and compliance.

What You’ll Own

Technical Direction & Delivery

• Drive architecture and technical strategy for enterprise security products.
• Contribute meaningfully to the codebase while guiding engineering standards and quality.
• Deliver key roadmap milestones, including advanced DLP capabilities and real-time SIEM integrations.
• Ensure security services meet strict uptime, compliance, and audit requirements.

Team Leadership & Growth

• Build and develop a high-performing engineering team focused on enterprise security.
• Establish clear ownership, execution standards, and performance expectations.
• Create clarity in ambiguous spaces and guide the team toward measurable outcomes.

Product & Business Impact

• Partner closely with Product to define and prioritize initiatives based on enterprise customer needs.
• Align engineering efforts with adoption, deal velocity, and revenue impact.
• Help shape Enterprise Security as a distinct and strategic product area within the broader platform.

What You Bring

• Proven experience building enterprise security products for IT administrators and security leaders (e.g., DLP, SIEM integrations, audit systems, access controls, encryption, compliance tooling).
• Strong understanding of enterprise buyers, compliance requirements, and the operational expectations of security products.
• 5+ years of hands-on software engineering experience, ideally in modern web stacks (Node.js/TypeScript, React, or similar).
• 2+ years of experience managing and mentoring engineers, with a history of delivering complex, high-impact systems.
• Comfort operating in high-visibility environments where reliability and trust are non-negotiable.
• Experience leveraging AI tools to accelerate development workflows or a strong interest in adopting them.
• Excellent remote collaboration skills, with experience leading distributed teams through clear documentation and async communication.

Nice to Have

• Experience working with enterprise compliance frameworks such as SOC 2, FedRAMP, or GDPR.
• Familiarity with integrations across enterprise security ecosystems (e.g., SIEM platforms and monitoring tools).
• Background in companies evolving from SMB-focused offerings to enterprise-scale solutions.

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Machine Learning Engineer – GenAI (Remote)

Location: Remote (U.S.)
Compensation: Up to $250K

The Role

We’re looking for a product-minded Machine Learning Engineer to help take GenAI ideas from zero to one. This role is for someone who enjoys ambiguity, thinks in terms of user impact, and knows how to turn early concepts into real, shipped AI products.

You’ll sit at the intersection of ML engineering, product strategy, and execution, owning problems end-to-end – from defining what to build to deploying it in production.

What You’ll Do

• Build, fine-tune, and deploy GenAI, LLM, and RAG-powered features used by real customers.

• Own 0→1 product development, translating fuzzy ideas into shipped ML systems.

• Partner closely with product, design, and engineering to define requirements, success metrics, and tradeoffs.

• Prototype quickly, run experiments, and iterate based on real user feedback.

• Take models from notebook to production, owning pipelines, deployment, and monitoring.

• Help shape product direction by connecting ML capabilities to business and user outcomes.

What You’ll Bring

• 4+ years of experience building and deploying machine learning systems.

• Hands-on experience with GenAI / LLMs (RAG, embeddings, prompt design, fine-tuning).

• Strong product intuition – experience working closely with PMs or owning product decisions yourself.

• Proven experience delivering early-stage or 0→1 products.

• Strong Python skills and experience with modern ML frameworks.

• Excellent communication skills and comfort explaining technical tradeoffs to non-technical partners.

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ML Infrastructure Engineer

Location: Remote (US or UK)

About the Role

We’re looking for an ML Infrastructure Engineer to build and scale production systems for cutting-edge generative AI models. You’ll architect scalable inference pipelines, optimize model deployment, and ensure our 3D and multimodal generation systems run reliably at scale.

What You’ll Do

• Design and deploy high-performance backend systems for serving generative models in production
• Build and optimize GPU-based inference services with focus on latency, throughput, and cost efficiency
• Implement model optimization techniques including quantization, pruning, and distillation
• Develop robust APIs and microservices for model serving using FastAPI, Flask, or gRPC
• Manage cloud infrastructure and CI/CD pipelines for continuous model deployment
• Scale distributed inference systems to handle high-concurrency workloads with request batching
• Collaborate with ML researchers to productionize diffusion models, transformers, and multimodal pipelines

Required Experience

Generative AI Models

• Hands-on experience with diffusion models and transformer-based architectures
• Background in multimodal pipelines combining image and 3D generation
• Familiarity with 3D generation or computer graphics pipelines (meshes, textures, multi-view data)

Production Infrastructure

• Strong track record building backend and infrastructure systems in production environments
• Expert-level Python programming with production-grade API design
• Deep experience deploying and operating ML models at scale, including GPU-based inference services, concurrency handling, request batching, and latency/throughput optimization

ML Deployment Stack

• Proficiency with cloud platforms: AWS (SageMaker, EC2, EKS), GCP, or equivalent
• Experience with containerization (Docker), orchestration, and CI/CD pipelines
• Hands-on work with model optimization frameworks: ONNX Runtime, TensorRT, FSDP, DeepSpeed
• Knowledge of distributed systems and scalable inference frameworks (Ray, Triton, TorchServe)

Nice to Have

• Experience with real-time inference systems or streaming pipelines
• Background in graphics rendering or game engine technologies
• Contributions to open-source ML infrastructure projects
• Understanding of cost optimization strategies for GPU compute

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Machine Learning Engineer – GenAI / Azure

Location: remote (United States)

Compensation: Up to 250K

Unfortunately, this role does not offer sponsorship or can facilitate transfers at this time.

We are seeking a seasoned ML Engineer working on GenAI products with a core focus on end-to-end deployment.

What You’ll Do

• Build, fine-tune, and deploy LLM-powered and Retrieval-Augmented Generation (RAG) systems for production use cases.
• Design and maintain end-to-end ML pipelines covering data ingestion, training, evaluation, deployment, and monitoring.
• Productionize models using Azure-based services (e.g., Azure OpenAI, Azure AI Search, Azure ML, or equivalent tooling).
• Collaborate with product and engineering partners to define requirements, success metrics, and model behaviour in real applications.
• Optimize inference performance, reliability, and cost for large-scale, user-facing AI systems.
• Improve evaluation frameworks, feedback loops, and continuous learning workflows to raise model quality over time.
• Stay current with emerging GenAI techniques and help apply them pragmatically in production environments.

What you’ll Bring

• 5+ years of experience in Machine Learning with a core focus on RAG, LLM, and GenAI solutions
• Experience designing models and deploying them into production
• Extensive experience in Python
• Experience in a variety of ML tools like Huggingface, Pytorch, Tensorflow, OpenAI
• Strong skills with Azure
• Mentorship or leadership experience

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