machine engineer

Hyper Recruitment Solutions

<div>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We are currently looking for a Machine Learning Engineer to join a pioneering research organisation dedicated to advancing drug discovery through innovative approaches to disordered proteins. This is an exciting opportunity for a candidate with a strong industrial background and a passion for applying machine learning to complex biological problems. Based at their modern facility, you will play a key role in driving forward cutting-edge research in a dynamic, open-source environment.
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 <br/>
 In this position, you will be responsible for developing and deploying machine learning models specifically tailored to tackle the challenges presented by highly dynamic and disordered proteins, with a particular focus on NMR data. You will work independently within a small, autonomous team, influencing research directions and interpreting self-generated data to uncover new insights in this emerging scientific frontier.
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 <strong>
  Key Duties And Responsibilities
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  <br/>
 </strong>
 Your duties as the Machine Learning Engineer will be varied, however the key duties and responsibilities are as follows:
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 <br/>
 <ul>
  <li>
   Develop and implement machine learning models to analyse complex biological data, particularly focusing on disordered proteins.
  </li>
  <li>
   Collaborate with scientific teams to interpret data, draw insights, and refine experimental approaches based on model findings.
  </li>
  <li>
   Engage directly with real biological problems, balancing modelling expertise with practical, applied research.
  </li>
  <li>
   Use your technical knowledge to drive projects independently within a small, open-source environment, ensuring results are meaningful and impactful.
  </li>
  <li>
   As the Machine Learning Engineer, you will be pivotal in translating scientific challenges into effective computational solutions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Role Requirements
  <br/>
  <br/>
 </strong>
 To be successful in your application to this exciting role as the Machine Learning Engineer we are looking to identify the following on your profile and past history:
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 <br/>
 <ul>
  <li>
   A Degree or higher level in a relevant field (e.g., Computer Science, Data Science, Bioinformatics) with proven applied experience.
  </li>
  <li>
   Demonstrated industrial experience in developing machine learning solutions within biological or biochemical research settings.
  </li>
  <li>
   Strong understanding of disordered proteins, protein dynamics, and limitations of static techniques like NMR.
  </li>
  <li>
   Proven ability to work independently, drive projects forward, and influence research directions within small, autonomous teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  WHAT&rsquo;S IN IT FOR YOU?
  <br/>
  <br/>
 </strong>
 This is a rare opportunity to contribute to groundbreaking research in drug discovery at a forward-thinking, non-profit organisation. You will benefit from a collaborative, open-source environment with significant influence over scientific direction, paired with a competitive salary package and the potential for sponsorship if required. Working four days on-site offers excellent work-life balance, within a state-of-the-art facility supported by recent government funding.
 <br/>
 <br/>
 Key Words:
 <em>
  Machine Learning
 </em>
 /
 <em>
  Bioinformatics
 </em>
 /
 <em>
  Disordered Proteins
 </em>
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 <em>
  NMR
 </em>
 /
 <em>
  Applied Research
 </em>
 /
 <em>
  Autonomy
 </em>
 /
 <em>
  Biological Data Analysis
 </em>
 /
 <em>
  Open Source
 </em>
 /
 <em>
  Innovation
 </em>
 /
 <em>
  Drug Discovery
  <br/>
  <br/>
 </em>
 "Hyper Recruitment Solutions Ltd (HRS) is an Equal Opportunities employer. We welcome applications from anyone who meets the role requirements. HRS exclusively supports the STEM sectors, combining recruitment expertise with scientific knowledge to help you advance your career".
</div>


Machine Learning Engineer

Haystack

<div>
 We are working with a pioneering technology firm that is at the forefront of developing cutting-edge AI solutions for real-world applications across various industries. This company is renowned for its innovative approach to machine learning and its commitment to pushing the boundaries of what's possible.
 <br/>
 <br/>
 The Role
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 <br/>
 <ul>
  <li>
   Develop, train, and optimise advanced computer vision and machine learning systems
  </li>
  <li>
   Deploy machine learning solutions in constrained edge environments
  </li>
  <li>
   Work with a team of experts on innovative AI projects
  </li>
  <li>
   Contribute to the full lifecycle of machine learning model development
   <br/>
   <br/>
  </li>
 </ul>
 What You'll Need
 <br/>
 <br/>
 <ul>
  <li>
   Proven experience as a Machine Learning Engineer
  </li>
  <li>
   Expertise in computer vision and machine learning model development
  </li>
  <li>
   Familiarity with deploying models in edge environments
  </li>
  <li>
   Strong problem-solving skills and an analytical mindset
  </li>
  <li>
   Excellent communication and collaboration abilities
   <br/>
   <br/>
  </li>
 </ul>
 What's On Offer
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 <br/>
 <ul>
  <li>
   Competitive salary based on experience
  </li>
  <li>
   Opportunity to work on groundbreaking AI technology
  </li>
  <li>
   Diverse and inclusive work environment
  </li>
  <li>
   Professional growth and development opportunities
   <br/>
   <br/>
  </li>
 </ul>
 Apply via Haystack today!
 <br/>
 <br/>
</div>


Code Compass 🧭

<div>
 <p>
  🤖 Machine Learning Engineer &ndash; Computer Vision &amp; Generative AI &ndash; 100%
 </p>
 <p>
  <br/>
 </p>
 <p>
  📍 Berlin, Germany | 💰 &euro;50,000 - &euro;70,000 + Benefits | 🌍 Hybrid Working
 </p>
 <p>
  <br/>
 </p>
 <p>
  Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact.
 </p>
 <p>
  <br/>
 </p>
 <p>
  ⚙️ Tech Stack:
 </p>
 <p>
  Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows
 </p>
 <p>
  <br/>
 </p>
 <p>
  🚀 About the Role:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   As a Machine Learning Engineer, you will:
  </li>
  <li>
   Develop, train, and optimise machine learning models focused on computer vision and generative AI applications
  </li>
  <li>
   Build and deploy scalable ML solutions into production environments
  </li>
  <li>
   Design automation solutions that reduce manual effort and improve operational efficiency
  </li>
  <li>
   Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy
  </li>
  <li>
   Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions
  </li>
  <li>
   Research emerging technologies and rapidly evaluate their suitability for business applications
  </li>
  <li>
   Contribute to the evolution of production-grade machine learning infrastructure and workflows
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  ➕ Nice to Have:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Several years of hands-on experience within machine learning and computer vision
  </li>
  <li>
   Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow
  </li>
  <li>
   Practical experience working with generative AI technologies including diffusion models and GANs
  </li>
  <li>
   Understanding of ML deployment, scalability, performance optimisation, and production environments
  </li>
  <li>
   Experience with Docker and cloud-based infrastructure
  </li>
  <li>
   Knowledge of creative AI tools and visual content workflows
  </li>
  <li>
   Experience working with image-based products, digital content platforms, or related industries
  </li>
  <li>
   Strong analytical thinking combined with a pragmatic, solution-oriented mindset
  </li>
  <li>
   Ability to communicate effectively in an international and cross-functional environment
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  💪 Benefits:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Opportunity to work on cutting-edge AI and machine learning technologies
  </li>
  <li>
   Highly collaborative and innovative working environment
  </li>
  <li>
   Flexible working arrangements with hybrid options
  </li>
  <li>
   Exposure to challenging technical problems with real-world impact
  </li>
  <li>
   Professional development support, training, and continuous learning opportunities
  </li>
  <li>
   Modern working environment with strong team culture and regular social activities
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <em>
   ✉️ Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.
  </em>
 </p>
</div>


Stedin

<p></p><div><h2 class="jobSectionHeader"><b>Jouw energie in de plus</b></h2><p>
Als Machine Learning Engineer werk je op een state-of-the-art MLOps platform en bouw je mee aan complexe ML producten en data-oplossingen die direct bijdragen aan de energietransitie bij Stedin.</p><p><b><br>
Waarom werken bij Stedin jou energie oplevert:</b></p><ul><li><p>
Werken aan impactvolle ML-oplossingen voor de energietransitie.</p></li><li><p>
Veel ruimte voor innovatie, eigenaarschap en persoonlijke groei.</p></li><li><p>
Hybride werken met een sterk team en moderne tech stack (Azure, Databricks).</p></li></ul><h2 class="jobSectionHeader"><b><br>
Werk om trots op te zijn</b></h2><p>
Als machine learning engineer denk je mee over de inrichting van het platform en zorg je ervoor dat ML oplossingen er vlekkeloos op draaien. Hiermee draag je bij aan het betrouwbaar en toekomstbestendig maken van ons energienet. Je helpt data scientists binnen heel Stedin met het operationaliseren van hun modellen en zorgt dat ze schaalbaar en robuust draaien. Daarmee lever je direct impact op de energietransitie.</p><p><b><br>
Een dag als Machine Learning Engineer</b></p><ul><li><p>
Je start met de daily stand-up en stemt af met data scientists en engineers.</p></li><li><p>
Je ontwikkelt en verbetert machine learning modellen en zet deze live binnen het platform.</p></li><li><p>
Je werkt aan pipelines, MLOps en schaalbaarheid van modellen.</p></li><li><p>
Je spart met collega&rsquo;s over technische oplossingen en nieuwe idee&euml;n.</p></li><li><p>
Je helpt minder ervaren collega&rsquo;s groeien in techniek en structuur.</p></li></ul><h2 class="jobSectionHeader"><b><br>
Hier laad jij van op</b></h2><p>
Alle financi&euml;le arbeidsvoorwaarden op een rij:</p><ul><li><p>
Een bruto maandsalaris tot &euro; 7.124,60 (bij 40 uur), 24,5 vakantiedagen en pensioenopbouw bij ABP.</p></li><li><p>
Een persoonlijk budget van 24% bovenop je salaris (incl. vakantiegeld), vrij te besteden.</p></li><li><p>
Een laptop en telefoon of een BYOD-vergoeding.</p></li></ul><p></p><p>
Daar komt dit nog bovenop:</p><ul><li><p>
Moderne thuiswerkfaciliteiten en een thuiswerkvergoeding van &euro; 2,40 per dag. Bij Stedin werken we 50% thuis en 50% op kantoor.</p></li><li><p>
Reizen naar kantoor doe je met de ov-vrijregeling. Dat is een ov-kaart die je ook in je vrije tijd kan gebruiken. Of met de flexibele reisregeling, waarbij je zelf kiest, combineert en varieert hoe je naar je werk reist en een extra vergoeding krijgt als je met de fiets komt.</p></li><li><p>
Jouw ontwikkeling staat centraal: events bezoeken met collega&rsquo;s en trainingen en opleidingen volgen. Zo haal jij het beste uit jezelf.</p></li></ul><h2 class="jobSectionHeader"><b><br>
Vol energie vooruit met team Data Science &amp; Engineering</b></h2><p>
Je werkt in het Machine Learning team binnen het Data Office. Hier werk je samen met data scientists en engineers die allemaal dezelfde drive delen: impact maken met data. De sfeer is open en informeel, met veel ruimte om idee&euml;n te delen en van elkaar te leren. Minstens twee keer per week werk je samen op kantoor in Rotterdam, naast station Blaak. Daarnaast zijn er nog talloze leuke activiteiten of initiatieven zoals borrels, sportactiviteiten, Jong Stedin, F-empower of NetAnders.<br>
<br>
<b>Met deze kwaliteiten groei jij hier verder</b></p><p>
Je bent analytisch sterk en denkt in oplossingen. Je pakt eigenaarschap, werkt gestructureerd en weet anderen mee te nemen in jouw idee&euml;n. Daarnaast ben je communicatief vaardig en deel je actief kennis binnen het team.</p><p></p><p>
Verder heb je:</p><ul><li><p>
Minimaal 2 jaar ervaring als machine learning engineer of in een vergelijkbare rol.</p></li><li><p>
Sterke programmeervaardigheden in Python en ervaring met schaalbare ML-oplossingen.</p></li><li><p>
Ervaring met Azure (Databricks, ADLS), MLOps en tools zoals Kubernetes, Airflow en Spark.</p></li><li><p>
Voor deze functie is uitstekende beheersing van de Nederlandse taal op minimaal B2‑niveau vereist, in spreken, lezen, schrijven &eacute;n begrijpen.</p></li></ul><p></p><p><b><br>
Zet de stap naar jouw volgende uitdaging</b></p><p>
Zin om met jouw werk echt impact te maken op de energietransitie? Solliciteer direct via de knop.</p><p></p><p><b>
Goed om te weten:</b></p><ul><li><p>
Je werkt in principe minimaal 40 uur per week. Wil je er meer uithalen? 36 of 32 uur is ook een optie.</p></li><li><p>
Solliciteren kan tot 5 juli. De eerste gesprekken vinden plaats op 8 en 10 juli bij ons op kantoor aan de Blaak.</p></li><li><p>
Een (pre) employment screening en assessment maken onderdeel uit van het proces.</p></li></ul>
Solliciteer direct</div>
<br><div><div><h2 class="jobSectionHeader"><b>De plussen van deze baan</b></h2><p></p>
</div><div><ul><li>50% thuiswerken met &euro;750,- voor jouw thuiswerkplek</li>
<li>Iedere maand je persoonlijk budget kiezen van 24%</li>
<li>Mooie techniek, veel uitdaging &eacute;n maatschappelijke impact</li>
<li>Volop mogelijkheden om te groeien</li></ul></div></div>
<br><div></div><div><div><div><div><h2 class="jobSectionHeader"><b>Zo solliciteer je voor deze functie</b></h2>
<p>In een paar stappen naar je baan!</p>
</div><div><p>Solliciteren</p>
<div>Je solliciteert via onze website. Onder de vacature vind je een knop met een digitaal sollicitatieformulier, waarin je je cv en motivatie kunt uploaden.
</div><p>Ontvangstbevesting</p>
<div>Na je sollicitatie ontvang je een automatische bevestiging per e-mail. Niet ontvangen? Controleer je spamfilter of je ongewenste e-mail. Of neem even contact met ons op.
</div><p>Eerste selectie</p>
<div>Wij bekijken je cv en motivatie. Als die aansluit bij de vacature, nodigen we je uit voor de volgende stap.
</div><p>Selectiegesprek</p>
<div>Je eerste gesprek is altijd met een aantal toekomstige collega&rsquo;s. Dit kan een leidinggevende, recruiter of aanstaande collega zijn. We bespreken je kennis, ervaring en ontwikkelmogelijkheden. Dat laatste is belangrijk, omdat door de energietransitie alles razendsnel verandert. We vertellen natuurlijk ook wat we jou te bieden hebben. Geloven we dat er een klik is, dan volgt er een vervolggesprek.
</div><p>Online assessment</p>
<div>Voor sommige functies maak je een online assessment. Daarin testen we je capaciteiten, persoonlijkheidskenmerken en ontwikkelmogelijkheden. Als er een match is, nodigen we je uit voor een gesprek.
</div><p>Voorstel arbeidsvoorwaarden</p>
<div>Is er na het vervolggesprek nog steeds die perfecte match, dan ontvang je een arbeidsvoorwaardenvoorstel. Zeg jij &rsquo;JA&rsquo;, dan zeggen wij &rsquo;WELKOM&rsquo; en gaan we samen veel moois doen.
</div><p>Screeningsbeleid</p>
<div>Wij verwachten van elkaar dat we altijd betrouwbaar en integer zijn. Dat we handelen in het belang van onze mensen, onze organisatie en onze klanten. Om deze betrouwbaarheid en integriteit zoveel mogelijk te garanderen, voeren wij een screeningsbeleid. Dit betekent dat we van nieuwe collega&rsquo;s een Verklaring Omtrent het Gedrag (VOG) vragen. Je ontvangt van ons een instructie hoe je deze kunt aanvragen. Voor sommige functies geldt een screeningsplicht. Dit betekent dat er een uitgebreide screening wordt gedaan.
</div></div></div></div><div></div><div><div><div>Vragen? Stel ze aan Marloes Cassuto +31 (6) 15297058 Marloes.Cassuto@stedin.net</div></div></div></div>

IC Resources

<div>
 I&rsquo;m working with a deep‑tech startup specialising in machine learning, building next‑generation tools to transform how complex integrated circuits are verified. Their technology accelerates simulation coverage and reduces tapeout risk &mdash; giving chip design teams a step‑change in capability.
 <br/>
 <br/>
 This is a high‑impact opportunity for a Machine Learning Engineer looking to make a difference in silicon.
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 <br/>
 <strong>
  What They&rsquo;re Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   First degree in relevant STEM subject
  </li>
  <li>
   3+ years in industry building production ML systems
  </li>
  <li>
   Python + PyTorch/JAX expertise for training, inference, and model export
  </li>
  <li>
   Experience building data pipelines for complex scientific/engineering datasets
  </li>
  <li>
   Solid software engineering fundamentals &mdash; testing, CI/CD, clean APIs
  </li>
  <li>
   End‑to‑end ML system ownership from data ingestion to model deployment
  </li>
  <li>
   Clear communication &mdash; writing specs, documenting APIs, presenting to customers
  </li>
  <li>
   Familiarity with circuit simulation or EDA tools (nice to have)
  </li>
  <li>
   C++/CUDA experience for performance‑critical components (nice to have)
  </li>
  <li>
   Startup or fast‑moving team experience
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Consider It
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary, bonus, and meaningful equity
  </li>
  <li>
   Flexible remote/hybrid setup with London/Cambridge/Oxford bases
  </li>
  <li>
   Support for learning and development
  </li>
  <li>
   Close collaboration with researchers and exposure to real customer workflows
  </li>
  <li>
   Your work ships to real semiconductor customers and runs inside production chip‑design tools
   <br/>
   <br/>
  </li>
 </ul>
 Please contact Chris Amison for more information.
</div>


IMC Trading

<div>
 As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.
 <br/>
 <br/>
 This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC&rsquo;s technology and trading capabilities.
 <br/>
 <br/>
 <strong>
  Your Core Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   The opportunity to be in a brand new position in a growing team
  </li>
  <li>
   Develop large-scale distributed training pipelines to manage datasets and complex models
  </li>
  <li>
   Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
  </li>
  <li>
   Develop libraries to improve the performance of machine learning frameworks
  </li>
  <li>
   Maximize performance in training and inference using GPU hardware and acceleration libraries
  </li>
  <li>
   Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
  </li>
  <li>
   Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
  </li>
  <li>
   Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
  </li>
  <li>
   Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
  </li>
  <li>
   Dig into the internals of open-source ML tools to extend their capabilities and improve performance
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your Skills And Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   5+ years of experience in machine learning with a focus on training or inference systems
  </li>
  <li>
   Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
  </li>
  <li>
   Strong engineering skills, including Python, CUDA, or C++
  </li>
  <li>
   Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
  </li>
  <li>
   Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
  </li>
  <li>
   Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
  </li>
  <li>
   Exposure to cloud platforms and orchestration tools
  </li>
  <li>
   A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we&rsquo;ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.
</div>


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