Machine Learning Engineer Place of work: Abu Dhabi, United Arab Emirates
About Role: Insilico Medicine is seeking a Machine Learning Engineer to develop, support and improve predictive models and retrosynthesis in Chemistry & Biology. The candidate will write production-level Python code, run ML experiments, integrate new functionalities, and work with foundation models. The candidate will also provide technical support to the DevOps team and perform intra-team MLOps.
Reports to: Team Lead in Cheminformatics
Responsibilities:
- Develop and maintain the internal machine learning pipeline at production level to support drug discovery initiatives.
- Optimize, refactor, and debug existing Python code to enhance performance, scalability, and efficiency.
- Deploy ML models into the platform for real-world applications in chemistry and biology.
- Implement and fine-tune ML-dedicated algorithms in Python, ensuring high accuracy and robustness.
- Collaborate on MLOps practices to ensure seamless model integration, deployment, and continuous improvement.
Education: Bachelor's, Master's, or PhD in a Machine Learning related field.
Experience and Skills:
- Strong background in machine learning with practical application experience.
- 4+ years of experience in Python production-level development.
- Proficiency with coding standards such as PEP8 and Google style guide.
- Experience with NoSQL databases such as MongoDB.
- Experience working with Linux or other Unix-based operating systems.
- Proficiency in version control systems like Git.
- Hands on experience with NumPy, Pandas, PyTorch, and scikit learn.
- Solid understanding of object-oriented programming, design patterns, and software architecture best practices.
- Proactive attitude, strong problem solving skills, and commitment to continuous learning.
Preferred Skills:
- Experience with deep learning frameworks and techniques.
- Familiarity with RDKit for cheminformatics and Plotly for data visualization.
- Hands on experience with Transformers, RNNs, CNNs, GNNs, and Gradient Boosting.
- Expertise in feature engineering and optimization techniques.
- Knowledge of cheminformatics and the drug discovery process.
- Ability to quickly learn and adapt to new libraries, tools, and emerging ML technologies.
- Experience in programming with C++ is an advantage.
Please send your CV to
Senior Machine Learning Scientist Place of work: TBD
About Role: We are seeking a Senior Machine Learning Scientist with expertise in modern generative modelling and structure aware machine learning to develop advanced AI systems for modelling complex three dimensional molecular data. The role involves building deep learning approaches that operate on spatial molecular representations, integrating physical and geometric constraints, and supporting computational workflows.
Reports to: Head of AI for Chemistry Solutions
Responsibilities:
Model Research & Development:
- Develop ML models to analyze 3D molecular structures and interactions.
- Design computational workflows to evaluate and prioritize candidate structures based on predicted structural and physicochemical properties.
- Build architectures that integrate multiple predictive tasks across structural modelling and interaction prediction.
- Develop representations and embeddings for complex molecular geometries and spatial relationships.
- Work with large scale structural datasets.
Technical Leadership:
- Design scalable pipelines for training models on large structural datasets.
- Define modelling approaches that incorporate spatial context, interaction interfaces, and geometric constraints.
- Collaborate with engineers to ensure efficient training, inference, and integration into internal platforms.
Research & Strategy:
- Stay up to date with advances in protein design, molecular ML, and geometric deep learning.
- Evaluate emerging methods such as all atom diffusion models, graph networks, and multimodal foundation models.
- Contribute to internal research directions and experimentation with new modelling paradigms for complex spatial data.
Education: PhD or MS in Machine Learning, Computational Biology, Structural Biology, Computer Science, Biophysics, or related field.
Experience and Skills:
- Strong experience developing ML models operating on 3D spatial or geometric data, including diffusion based generative models, graph neural networks, equivariant neural networks (SE(3)/SO(3 , and transformer based architectures applied to structured data.
- Proficiency with PyTorch.
- Understanding of molecular structure, spatial interactions, and physical constraints in molecular systems.
- Experience working with coordinate based structural datasets and molecular data formats.
- Experience with distributed training, model optimization, and high performance compute environments.
- Strong software engineering practices (Git, testing, reproducibility).
Preferred Qualifications:
- Familiarity with modern ML approaches for macromolecular structure modelling and prediction, including systems such as AlphaFold.
- Exposure to emerging structure aware generative or modelling architectures in scientific ML.
- Experience with open source research systems used in structural modelling pipelines.
- Background in computational chemistry, structural biophysics, or molecular simulation.
- Experience developing geometry aware or constraint aware ML models.
- Contributions to open source ML or scientific computing projects.
Please send your CV to
Business Development Manager Place of work: Fully remote, open globally (Preferred: Japan, South Korea, Europe)
About Role: We are scaling our Business Development team and are looking for commercially strong, technically fluent BD Managers to shape the adoption of AI driven platforms globally. The role focuses on outbound pipeline development, strategic partnerships, and representing AI technologies at conferences.
Insilico is AI native, utilizing LLMs and AI agents for prospect research, segmentation, campaign personalization, follow ups, competitive analysis, and CRM optimization. Candidates should understand AI benchmarks and articulate performance metrics effectively.
Key Responsibilities:
- Collaborate with Line Manager to design and execute sales strategies, including targeted email campaigns.
- Identify target groups, build prospect lists, and generate qualified sales leads.
- Qualify interest through inbound lead follow up, outbound calling, and email outreach.
- Secure meetings and product demonstrations with prospects and existing customers.
- Handle follow up and drive completion of contractual documents.
- Work closely with Legal, AI, Chemistry, Biology, R&D, and Alliance Management teams.
- Represent Insilico's AI platforms at international conferences and industry events.
- Maintain disciplined CRM records and provide pipeline updates to senior management.
- Adjust outreach strategy based on evolving business priorities.
Required Experience:
- Industry Background: Experience in Big Pharma, biotech, or drug discovery, or AI solutions and data sales.
- Prior BD experience licensing or commercializing AI platform technologies.
- Commercial Capability: Demonstrated success in B2B sales with complex, multi stakeholder cycles.
- Proven ability to generate meetings and build a pipeline through outbound efforts.
- Experience selling complex technical platforms.
- Comfortable engaging scientific, technical, and executive audiences.
- Professional Skills: Strong communication, presentation, and networking; CRM discipline (Salesforce preferred); relevant graduate/postgraduate qualification preferred with interest in AI/ML in drug discovery.
AI & Benchmark Proficiency (Required):
- Solid understanding of large language models (LLMs).
- Actively using generative AI tools or AI agents to optimize workflow productivity.
- Ability to discuss AI driven drug discovery platforms credibly in both technical and commercial contexts.
- Strong interest in AI benchmarking frameworks and performance validation.
- Comfortable interpreting and communicating benchmark results and comparative model performance.
- Data driven mindset to differentiate validated performance from marketing claims.
Bonus Experience:
- Familiarity with Insilico's platforms (PandaOmics, Chemistry42, Generative Biologics, Science42, etc.).
- Experience in pharmaceutical contract negotiation.
- Background in AI driven drug discovery or computational platforms.
- Existing network within pharma BD or R&D leadership.
- Multilingual capabilities are a strong plus, particularly Japanese or Korean, and other major business languages in Europe and Asia.
Profile We're Looking For:
- Genuinely interested in Pharma.AI and platform technologies.
- Motivated by Insilico Medicine's work.
- Self starter with minimal supervision.
- Creative in sourcing and outreach strategies. . click apply for full job details