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Sr. Machine Learning Engineer

About Reliant

We believe that making the best decisions means looking at all the facts – a near-impossible task in our era of information overload. To fix this, we are building the next generation of machine learning software. Powered by generative AI, our algorithms analyze key information sources and provide comprehensive, factual answers for even your most complex queries.

We believe that the transformative impact of generative AI will be only realized by those willing to take on the world’s biggest information challenges. To make this future come true, we deploy our longstanding expertise in reinforcement learning and natural language processing.

We are scientists. Builders. Entrepreneurs. We spearheaded many of AI’s most impactful applications. We led teams at Google, DeepMind, and EY Parthenon. We now bridge cutting-edge AI research and the biopharma industry.

About the role

We are looking for a senior platform engineer with a strong track record working on applied ML (bonus points: in the life sciences). You will play a central role in defining and building out our ML and Data platform facilitating cutting-edge AI agents that excel at finding and organizing knowledge, and through your work lay the foundations of a new way of working with data.

If you are passionate about applying AI to real problems, enjoy working in a fast-paced environment, and are excited about contributing to the growth of an ambitious startup, this opportunity is for you.

As a key member of the machine learning team, you will

  • Work closely with the product and commercial teams to define AI-human collaborative workflows for the life sciences
  • Design and implement tooling and processes and tooling to benchmark against life sciences specific use cases that enable us to make rapid progress on key AI features
  • Design and implement tooling and processes allowing us to understand model performance in production
  • Design language model-powered data pipelines that scale to millions of documents
  • Optimize the performance of our data and LLM infrastructure
  • Train AI models specialized to specific information extraction and structuring work, optimizing for both accuracy, confidence, and performance
  • Build tooling around our ML and Data platform to facilitate an ergonomic developer experience.
  • Develop production-grade machine learning software

About you

As the ideal candidate, you have deep experience contributing to transformative machine learning applications. You are able to work end-to-end on machine learning applications and have an appreciation for automation, resiliency and proper tooling. You are a strong backend engineer with ample experience and interest in ML and Dev Ops.

You will thrive in this role if you bring the following skills and experiences:

  • A Master’s degree in Computer Science or related field (or equivalent experience), bonus if you have NLP or Reinforcement learning experience.
  • Demonstrated experience implementing practical ML algorithms and scaling them up to large-scale datasets
  • A strong ability to think creatively in a startup environment
  • Experience with CI/CD and Infrastructure as Code
  • 5+ years of experience developing in Python
  • Demonstrated experience with Pytorch, Jax, Tensorflow, or a similar framework
  • Excellent programming skills and ability to understand and design complex systems
  • Bonus: Experience applying AI to the life sciences or adjacent field

All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.



Développeur.se principal.e de plateforme ML (sciences biologiques)

Description du poste

Nous sommes à la recherche d’un.e ingénieur.e de plateforme spécialiste de l’apprentissage automatique (ML) appliqué (en sciences biologiques, un atout). Vous jouerez un rôle important dans l’élaboration et la conception de notre plateforme de ML et de données, alimentée par des agents d’IA de pointe maîtrisant l’art de trouver et de classer les connaissances. Votre travail servira à créer une nouvelle façon de tirer parti des données.

Vous aimez vous servir de l’IA pour résoudre des problèmes concrets? Vous prospérez dans les environnements dynamiques et avez envie de contribuer à la croissance d’une entreprise en démarrage ambitieuse? Alors, ce poste est pour vous!

En tant que membre clé de l’équipe ML, vous :

  • Travaillerez en étroite collaboration avec les équipes de produits et commerciales pour établir des flux de travail alliant la puissance de l’IA et de l’humain pour les sciences biologiques;
  • Créerez et mettrez en œuvre des outils et des processus à utiliser dans des cas d’usage précis dans le domaine des sciences biologiques pour favoriser le développement rapide des fonctions d’IA clés;
  • Concevrez et implanterez des outils et des processus pour nous aider à mesurer la performance du modèle en production;
  • Élaborerez des pipelines de données alimentés par des modèles de langage qui s’appliqueront à des millions de documents;
  • Optimiserez la performance de notre infrastructure de données et de grands modèles de langage (LLMs);
  • Entraînerez des modèles d’IA spécialisés dans l’extraction et la structuration de renseignements spécifiques afin d’optimiser leur précision, leur fiabilité et leur performance;
  • Élaborerez des outils pour notre plateforme d’apprentissage automatique et de données qui simplifieront l’expérience de développement;
  • Concevrez des logiciels d’apprentissage automatique de qualité production.

Profil recherché

Vous détenez une solide expérience de travail avec les applications d’apprentissage automatique transformatrices. Développeur.se backend chevronné.e, vous êtes en mesure de travailler de bout en bout sur des applications d’apprentissage automatique. L’automatisation, la résilience, les outils, l’apprentissage automatique ainsi que le développement et l’exploitation vous passionnent.

Ce poste vous convient si vous avez les qualifications suivantes :

  • Maîtrise en informatique ou dans un domaine connexe (ou expérience équivalente), et expérience en traitement automatique du langage naturel (NLP) ou en apprentissage par renforcement (RL), un atout;
  • Solide expérience dans la mise en œuvre d’algorithmes d’apprentissage automatique pratiques et dans leur développement pour des ensembles de données importants;
  • Grande capacité à faire preuve de créativité dans une entreprise en démarrage;
  • Expérience en intégration et en déploiement continus, ainsi qu’en infrastructure en tant que code;
  • Au moins 5 ans d’expérience en développement en Python;
  • Solide expérience avec Pytorch, Jax, Tensorflow ou tout autre cadre d’applications similaire;
  • Solides compétences en programmation et capacité à comprendre et à concevoir des systèmes complexes;
  • Expérience en application de l’IA aux sciences biologiques ou à un domaine connexe, un atout.

Toute candidature de personne qualifiée sera examinée, peu importe sa race, son origine ethnique, sa religion, son sexe, son identité de genre et son orientation sexuelle.

Average salary estimate

$135000 / YEARLY (est.)
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$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Sr. Machine Learning Engineer, Reliant AI

At Reliant, we are on a mission to revolutionize how we understand and process information through advanced machine learning. We believe in making informed decisions by looking at all the facts, and as a Sr. Machine Learning Engineer, you're at the forefront of this innovation. Here, you’ll have the opportunity to work with cutting-edge AI, leveraging reinforcement learning and natural language processing to create transformative applications, especially in the biopharma sector. Your role is pivotal in crafting and building our ML and Data platform, defining workflows that enable effective AI-human collaboration tailored for the life sciences. You'll get to design tooling for benchmarking life sciences use cases, optimize performance of our data and LLM infrastructure, and develop production-grade machine learning software. If you have a passion for solving real-world problems with AI, enjoy a fast-paced environment, and want to contribute to a groundbreaking startup journey, this is the perfect opportunity for you. At Reliant, we thrive on the creativity of our team members who can bring innovative solutions to the table, all while working alongside experts who have previously spearheaded AI applications at major tech companies. Join us in shaping a new era in data utilization and AI application where your contributions will drive our significant growth and impact.

Frequently Asked Questions (FAQs) for Sr. Machine Learning Engineer Role at Reliant AI
What responsibilities does a Sr. Machine Learning Engineer at Reliant have?

As a Sr. Machine Learning Engineer at Reliant, you will be responsible for defining and building our ML and Data platform. This entails designing workflows for AI-human collaboration in the life sciences, creating tools and processes for benchmarking against specific use cases, optimizing model performance in production, and developing scalable data pipelines. Your role is crucial in contributing to the overall success and advancement of our AI solutions.

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What qualifications do I need to apply for the Sr. Machine Learning Engineer position at Reliant?

To be considered for the Sr. Machine Learning Engineer role at Reliant, you should ideally have a Master's degree in Computer Science or a related field, along with substantial experience in machine learning applications. Skills in Python development, utilizing frameworks like PyTorch or TensorFlow, and experience with CI/CD practices are essential. A background in NLP or Reinforcement Learning and exposure to the life sciences will be a plus.

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How does Reliant implement AI in the life sciences as a Sr. Machine Learning Engineer?

At Reliant, as a Sr. Machine Learning Engineer, you will implement AI in the life sciences primarily by designing AI-human collaborative workflows and optimizing models that support knowledge extraction and structuring. Your expertise will enable the application of AI-driven insights that are crucial for effective decision-making in the biopharma sector, thus improving outcomes in data management and accessibility.

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What kind of projects can a Sr. Machine Learning Engineer expect to work on at Reliant?

As a Sr. Machine Learning Engineer at Reliant, you can expect to work on projects that focus on developing cutting-edge machine learning solutions, including building AI-powered data pipelines that handle millions of documents, implementing processes for model performance evaluation, and creating tools that enhance the developer experience. Your projects will play a significant role in advancing how data is leveraged in the life sciences and beyond.

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What is the company culture like for Sr. Machine Learning Engineers at Reliant?

Reliant fosters a dynamic and innovative company culture where creativity and collaboration are highly valued. As a Sr. Machine Learning Engineer, you'll work alongside passionate team members who are experts in various domains, encouraging an entrepreneurial spirit. The emphasis is on solving real-world challenges using AI, and your contributions will directly impact the company's success as we reshape the future of data utilization.

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Common Interview Questions for Sr. Machine Learning Engineer
Can you describe your experience with machine learning frameworks like PyTorch or TensorFlow?

When answering this question, focus on your hands-on experience with these frameworks, such as projects you have completed, specific techniques you've implemented, and how you utilized them to solve complex problems. Providing detailed examples will demonstrate your proficiency and understanding of machine learning applications.

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How do you approach optimizing machine learning models for production use?

Discuss your methodology for optimization, which may include techniques such as hyperparameter tuning, performance monitoring, and using statistical methods to assess model reliability. Highlight any tools or best practices you follow to ensure that models perform effectively in a production environment.

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What challenges have you faced while implementing machine learning solutions, and how did you overcome them?

Share specific challenges you’ve encountered, such as issues with data quality, scaling algorithms, or integration with existing systems. Explain your problem-solving approach, emphasizing your analytical skills and innovative thinking that led to successful outcomes.

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Describe a time you collaborated on a project with product or commercial teams. How did you ensure alignment?

Focus on your communication skills and ability to work cross-functionally. Provide a specific example where you actively engaged those teams to understand their requirements and how you translated these insights into actionable machine learning strategies that met project goals.

Join Rise to see the full answer
What is your experience with CI/CD and Infrastructure as Code?

Detail your familiarity with CI/CD practices and tools you’ve used, such as Jenkins or GitLab CI. Describe how these practices improve deployment efficiency and reliability in ML projects, and explain your understanding of Infrastructure as Code using tools like Terraform or CloudFormation.

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How do you ensure your machine learning models are robust and reliable?

Elaborate on methods you use to validate and test your models, such as cross-validation, A/B testing, and monitoring performance metrics in production. Emphasize the importance of reproducibility and regular model updates based on new data.

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Can you explain your experience with automation in machine learning workflows?

Discuss specific automation tools and techniques you've employed to streamline ML workflows. This could include automating data preprocessing, model training, or deployment tasks. Highlight how these improvements boost efficiency and consistency in your development process.

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What strategies do you use to stay updated with the latest machine learning trends and technologies?

Share your approach to staying informed about industry trends, such as attending conferences, engaging with online communities, or participating in research. Mention any relevant resources, such as journals or websites, that you follow to enhance your knowledge.

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How would you approach a project involving knowledge extraction from unstructured data?

Illustrate your understanding of the process of knowledge extraction, including natural language processing techniques. Describe the steps you would take, from data collection and preprocessing to model selection and evaluation, emphasizing your analytical and problem-solving skills.

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Why do you want to work at Reliant as a Sr. Machine Learning Engineer?

Convey your interest in Reliant's mission and vision regarding the application of AI in the life sciences, and how your skills align with their goals. Discuss your excitement about contributing to a company that's innovating at the intersection of technology and healthcare.

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Reliable answers to business-critical questions, for the most demanding of data workflows.

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Full-time, remote
DATE POSTED
March 22, 2025

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