First-class IT Recruitment Solutions

---

Senior Machine Learning Engineer

6 Months+ Contract (outside IR35)

Remote

On behalf of a global pharmaceutical organisation, I am seeking a Senior AI/ML Engineer to help design, scale, and deploy advanced machine learning solutions that support the next generation of drug discovery.
You will work closely with AI/ML scientists and life-science experts, transforming exploratory research into robust, production-grade ML pipelines. You will play a pivotal role in strengthening MLOps practices, improving scalability and reliability, and ensuring that innovative ideas deliver real-world scientific impact.

If you are excited by applying AI at scale in a complex scientific environment—and want to help shape the future of AI/ML in the pharmaceutical industry—this could be your next contract!

The Role:

• Collaborate directly with AI/ML scientists to optimise models and deploy solutions into production, acting as an internal consultant from prototype to platform.
• Design and document blueprints and best practices for transitioning research code into scalable, maintainable ML systems.
• Explore, analyse, and visualise data to understand distributions and identify risks to model performance in real-world deployment.
• Ensure high data quality and model reliability through data cleaning, validation strategies, and systematic testing.
• Build and maintain training pipelines and reusable ML components that support scalable, repeatable ML.
• Contribute to education and upskilling across teams, raising overall MLOps and ML engineering maturity.

Skills/Experience required:

• A collaborative, technically strong engineer with a positive mindset and a passion for applied machine learning.  
• PhD or Master's degree with relevant experience, or a Bachelor's degree with strong hands-on expertise.
• Experience working closely with data scientists, data engineers, and life scientists.
• Previous experience in a healthcare or life-science organisation is advantageous, but not essential.
• Excellent communication skills, with the ability to explain complex technical topics to diverse audiences.
• You will be highly experienced with the following:

1. Programming & ML tooling: Advanced Python skills; hands-on experience with scikit-learn, Pandas, PyTorch, Jupyter, and ML pipelines.
2. Data & platform tools: Practical knowledge of Databricks, Ray, vector databases, Kubernetes, and workflow orchestration tools such as Apache Airflow, Dagster, or Astronomer.
3. GPU & scalable infrastructure: Experience with GPU computing on-premise and/or in the cloud, including DGX systems or cloud platforms such as AWS (EKS, SageMaker) and Azure (Azure ML, AKS); familiarity with ML platforms like MLflow, ClearML, or Weights & Biases.
4. Cloud & MLOps: Strong understanding of AWS, Azure, containerisation, Kubernetes, DevOps automation, and end-to-end ML lifecycle practices.
5. Data handling: Proven ability to wrangle, process, integrate, and analyse large, heterogeneous datasets, ideally in drug discovery or biomedical contexts.
6. LLMs & generative AI: Experience with large language models, including fine-tuning, pretraining or continued pretraining, inference, RAG pipelines, and multi-agent workflows using tools such as LlamaIndex, LangChain, and vector databases.
7. Production ML: Demonstrated success building, training, and deploying production-grade machine learning models in industry and/or academic research environments.

Please apply online with your CV.

---

---

Senior Machine Learning Engineer

6 Months+ Contract (outside IR35)

Remote

The Role:
On behalf of a global pharmaceutical organisation, I am seeking a Senior Machine Learning Engineer to help scale and operationalise AI/ML innovation. You will work at the interface of cutting-edge data science and robust engineering, partnering closely with AI/ML scientists to transition exploratory research into production-ready, repeatable ML solutions.

This is an amazing opportunity to immerse yourself in a vibrant tech ecosystem while contributing to the transformation of AI/ML in the pharmaceutical industry.

Role Responsibilities:

• Partner directly with AI/ML scientists to optimise models and deploy solutions into production, acting as an internal consultant from prototype to platform.
• Translate exploratory work into robust ML pipelines, creating blueprints and best practices for scalable, repeatable machine learning.
• Explore, analyse, and visualise data to understand distributions and identify issues that may impact real-world model performance.
• Ensure data quality and model reliability through validation strategies, cleaning pipelines, and systematic testing.
• Build and improve training pipelines and reusable ML components, addressing errors and technical debt.
• Collaborate with ML Infrastructure engineers to co-develop ML platforms, strengthen MLOps capabilities, and upskill teams across the organisation.
   

Skills/Experience required:

• You are a technically strong, collaborative engineer with experience working alongside data scientists and life-science researchers.
• PhD or Master's degree with relevant experience, or a Bachelor's degree with strong, hands-on expertise in ML engineering.
• Experience working in a healthcare or life-science environment would be advantageous, but not essential.
• Advanced Python skills and hands-on experience with data analytics and deep learning tools such as scikit-learn, Pandas, PyTorch, Jupyter, and ML pipelines.
• Practical experience with modern data and ML tooling, including Databricks, Ray, vector databases, Kubernetes, and workflow orchestrators such as Apache Airflow, Dagster, or Astronomer.
• Experience with GPU computing, on-premise and/or in the cloud, and building end-to-end scalable ML infrastructure.
• Strong knowledge of AWS and/or Azure, containerisation, Kubernetes, automation/DevOps, and the full ML lifecycle.
• Practical expertise in data wrangling and integration of large, heterogeneous datasets relevant to drug discovery.
• Hands-on experience with large language models, including fine-tuning, DPO, training, hosting, RAG pipelines, vector databases, and multi-agent systems.
• A proven track record of building, training, and deploying production-grade ML models in industry and/or academic research.

---

---

Principal Computer Vision Scientist 
6 Months+ Contract (outside IR35)
Remote

The Role
On behalf of a global organisation, I am seeking a Principal Computer Vision Scientist to lead the development of foundation models for biological imaging, with the ambition of accelerating target and biomarker discovery in early drug research. 

This role is pivotal in establishing a deeply integrated, multimodal AI framework, using cellular imaging as a core modality alongside molecular data, transcriptomics, and biomedical literature. You will play a pivotal role in shaping how generative AI is applied across Research & Early Discovery, helping to shorten the path from target identification to clinical impact; an exciting opportunity to be at the forefront of integrating AI and machine learning with biological data to drive scientific discovery. 

Key Responsibilities: 

• Lead the design, development, and deployment of next-generation AI/ML models for cellular imaging and multimodal biological data.
• Define and drive the strategy for integrating generative AI into early-stage drug discovery, working closely with cross-functional research teams.
• Advance state-of-the-art methods in computer vision, deep learning, representation learning, and multimodal foundation models.
• Communicate scientific results through internal reports, executive presentations, and peer-reviewed publications.
• Build and nurture collaborations with academic and industry partners.

Skills/Experience required:

• PhD in Computer Science, Bioinformatics, Computational Biology, Physics, or a related field.
• Hands-on experience pretraining or fine-tuning foundation models for computer vision.
• A strong publication record at leading conferences such as CVPR, NeurIPS, ICLR, or ICML.
• Proven expertise in multimodal representation learning, ideally applied to biological or pharmaceutical data.
• Advanced Python skills and deep experience with PyTorch, Hugging Face, PyTorch Lightning, or similar frameworks.
• Proficiency in modern software engineering practices, including Git, CI/testing, and contemporary Python tooling (e.g. uv).
• The ability to lead independent research while thriving in a highly collaborative, multidisciplinary environment.
• Excellent written and verbal communication skills.
• Experience in one or more of the following would be an advantagous:

1. High-content screening, high-throughput perturbative experiments, single-cell RNA-seq, or related data modalities.
2. Large-scale model training and deployment using cloud platforms (AWS, Azure, Nvidia DGX Cloud).
3. Systems modeling, biophysics, or causal inference in computational biology.
4. Writing well-tested, well-documented ML code, following best practices for maintainable research software.

Please apply online with your CV.
 

---