Machine Learning Engineer

In Technology Group
Oxford
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer (Azure Synapse) - London

Data Scientist

AI) Machine Learning Research Engineer

Data Science Engineer

AI Engineer - Jan 25

Data Engineer

This range is provided by In Technology Group. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from In Technology Group

Head of Data, BI, and AI @ In Technology Group.

Job Title: Machine Learning Engineer (Medical & Drug Discovery)

Location: Oxford (2 days a week onsite)

Salary: Flexible (Up to £80,000 DOE)

This one is for one of my best clients who is at the forefront of innovation in the medical and drug discovery sector. They are genuinely dedicated to leveraging cutting-edge machine learning techniques to accelerate breakthroughs in healthcare. If you’re passionate about using AI to solve complex biological and pharmaceutical challenges, join our team to help shape the future of medicine.

Job Description:

As a Machine Learning Engineer specializing in the medical and drug discovery domain, you’ll design, implement, and optimize AI models that drive innovation in biomedical research. You will work closely with data scientists, bioinformaticians, and domain experts to turn vast datasets into actionable insights.

Key Responsibilities:

  • Develop, train, and deploy machine learning models for tasks such as protein structure prediction, drug-target interaction, and biomarker discovery.
  • Engineer data pipelines to handle large-scale biomedical datasets, including genomics, clinical trials, and molecular data.
  • Implement and optimize deep learning architectures (e.g., CNNs, RNNs, transformers) for biological sequence analysis and imaging data.
  • Apply NLP models to process biomedical literature and clinical data.
  • Collaborate with cross-functional teams, including biologists and chemists, to define requirements and ensure model outputs align with scientific goals.
  • Monitor model performance and retrain as necessary to improve accuracy and generalization.
  • Stay current on advancements in ML, bioinformatics, and drug discovery to continuously enhance our models.

Requirements:

  • Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or a related field.
  • Strong proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Experience with specialized bioinformatics tools and libraries (e.g., Biopython, RDKit, DeepChem).
  • Solid understanding of statistical models, deep learning architectures, and data preprocessing techniques.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Knowledge of databases (SQL, NoSQL) and data engineering for large, diverse datasets.
  • Excellent problem-solving skills and ability to collaborate with interdisciplinary teams.
  • Strong communication skills, with the ability to convey technical results to non-technical audiences.

Preferred Qualifications:

  • Experience with generative models (e.g., GANs, VAEs) for molecule generation.
  • Knowledge of molecular docking, cheminformatics, or systems biology.
  • Exposure to regulatory considerations and data privacy in healthcare AI.

Join and contribute to transforming healthcare through AI-powered discoveries. Your work could be the key to the next breakthrough drug or lifesaving treatment.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Analyst, Information Technology, and Research

Industries

Biotechnology Research, Research Services, and Pharmaceutical Manufacturing

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.