Enigma
About the Company
Here at Enigma, we specialize in Generative AI recruitment, specifically focused on Machine Learning and Software Engineering disciplines. With a combined experience of 20+ years, we understand the intricacies of finding the perfect role as well as the right talent for your team.
But what sets Enigma apart? Our consultative approach. We don't just match candidates with job openings; we guide candidates, founders, and hiring managers through the recruitment process. Our value-added services go beyond traditional recruitment efforts, offering services such as recruitment process structuring, salary benchmarking, share allocation, CV reviews and so much more.
We're more than recruiters – we're partners in your success journey. Our mission is not only to connect you with exceptional talent and companies but also to support your growth and success every step of the way. We're committed to your success. Let us partner with you to connect you with people and companies alike, that will drive growth and innovation for years to come.
Listed Jobs
- Company Name
- Enigma
- Job Title
- Machine Learning Research Scientist | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
- Job Description
-
Machine Learning Research Scientist | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
We are looking for multiple highly skilled machine learning researchers with strong expertise in generative modeling is sought to join an interdisciplinary team of machine learning experts, protein engineers, and biologists. The team collaborates to transform how biology is controlled and diseases are cured. The role involves architecting innovative generative models aimed at designing new proteins that demonstrate functionality in wet lab assays.
This company specializes in developing generative AI models for synthetic biology, focusing on designing and reprogramming biological systems, including gene editing technologies to enable treatments for complex genetic diseases. Operating at the intersection of AI and biology, the team is driven by innovation, curiosity, and a commitment to creating significant positive global impact.
Requirements
Expertise in generative modeling: The ideal candidate has a proven track record in machine learning, with experience leading or contributing to high-profile projects, as evidenced by widely used open-source libraries, major product launches, or impactful publications (e.g., NeurIPS, ICML, ICLR, or Nature).
Skilled in ML development: They write robust, maintainable ML code, have proficiency in version control and code review systems, and are capable of producing high-quality prototypes and production code. They have experience running models on cloud hardware and parallelizing data and models across accelerators.
Data engineering capabilities: The candidate is experienced in building ML data pipelines for training and evaluating deep learning models, including raw data analysis, dataset management, and scalable pipeline construction.
Passion for optimization: They possess in-depth knowledge of ML libraries, hardware interactions, and optimization techniques for model training, inference speed, and validation metrics performance.
Mission-driven and curious: Motivated by the opportunity to make a positive global impact, they approach problems with relentless curiosity and adaptability.
Adaptability in dynamic environments: They thrive in fast-paced settings, achieving goals efficiently and effectively.
Desired Qualifications
Experience in computational biology or protein design: Experience with ML-driven projects in biology is advantageous.
Natural science background: Academic training in fields like physics, biology, or chemistry is a plus.
Key responsibilities
Develop machine learning models with real-world applications (~90%):
Curate and manage training and evaluation data.
Design and implement ML evaluation metrics aligned with organizational goals.
Rapidly prototype generative models and perform detailed analyses of their performance.
Collaborate with researchers, engineers, and designers, maintaining a high-quality codebase.
Support the maintenance of compute and ML infrastructure.
Coordinate with biology teams for wet lab testing campaigns and conduct model inferences for biological target testing.
Incorporate feedback from wet lab results to refine and improve models.
Engage in self-development (~10%):
Stay updated on the latest ML research and advancements.
Develop a strong understanding of protein and cell biology.
Share knowledge by organizing and presenting in reading groups or at conferences.
Excellent compensation - six figures+ & equity
Hybrid Working – 3 days p/w onsite. Central London
Permanent position
If you are interested in finding out more about this hire please reach out to tom@enigma-rec.ai for immediate consideration.
Machine Learning Research Scientist | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
London, United Kingdom
Hybrid
27-12-2024
- Company Name
- Enigma
- Job Title
- Machine Learning Research Engineer | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
- Job Description
-
Machine Learning Research Engineer | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
We are looking for multiple highly skilled machine learning research engineers with strong expertise in generative modeling is sought to join an interdisciplinary team of machine learning experts, protein engineers, and biologists. The team collaborates to transform how biology is controlled and diseases are cured. The role involves architecting innovative generative models aimed at designing new proteins that demonstrate functionality in wet lab assays.
This company specializes in developing generative AI models for synthetic biology, focusing on designing and reprogramming biological systems, including gene editing technologies to enable treatments for complex genetic diseases. Operating at the intersection of AI and biology, the team is driven by innovation, curiosity, and a commitment to creating significant positive global impact.
Requirements
Expertise in generative modeling: The ideal candidate has a proven track record in machine learning, with experience leading or contributing to high-profile projects, as evidenced by widely used open-source libraries, major product launches, or impactful publications (e.g., NeurIPS, ICML, ICLR, or Nature).
Skilled in ML development: They write robust, maintainable ML code, have proficiency in version control and code review systems, and are capable of producing high-quality prototypes and production code. They have experience running models on cloud hardware and parallelizing data and models across accelerators.
Data engineering capabilities: The candidate is experienced in building ML data pipelines for training and evaluating deep learning models, including raw data analysis, dataset management, and scalable pipeline construction.
Passion for optimization: They possess in-depth knowledge of ML libraries, hardware interactions, and optimization techniques for model training, inference speed, and validation metrics performance.
Mission-driven and curious: Motivated by the opportunity to make a positive global impact, they approach problems with relentless curiosity and adaptability.
Adaptability in dynamic environments: They thrive in fast-paced settings, achieving goals efficiently and effectively.
Desired Qualifications
Experience in computational biology or protein design: Experience with ML-driven projects in biology is advantageous.
Natural science background: Academic training in fields like physics, biology, or chemistry is a plus.
Key responsibilities
Develop machine learning models with real-world applications (~90%):
Curate and manage training and evaluation data.
Design and implement ML evaluation metrics aligned with organizational goals.
Rapidly prototype generative models and perform detailed analyses of their performance.
Collaborate with researchers, engineers, and designers, maintaining a high-quality codebase.
Support the maintenance of compute and ML infrastructure.
Coordinate with biology teams for wet lab testing campaigns and conduct model inferences for biological target testing.
Incorporate feedback from wet lab results to refine and improve models.
Engage in self-development (~10%):
Stay updated on the latest ML research and advancements.
Develop a strong understanding of protein and cell biology.
Share knowledge by organizing and presenting in reading groups or at conferences.
Excellent compensation - six figures+ & equity
Hybrid Working – 3 days p/w onsite. Central London
Permanent position
If you are interested in finding out more about this hire please reach out to tom@enigma-rec.ai for immediate consideration.
Machine Learning Research Engineer | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN
London, United Kingdom
On site
27-12-2024
- Company Name
- Enigma
- Job Title
- Contract Senior Software Engineer | Python | Go | C# | AWS
- Job Description
-
Contract Senior Software Developer – Python, Go, C#, AWS & Microservices – Contract Software Developer
Enigma have partnered with an exciting DeepTech Startup who are looking for an experienced Senior Software Engineer with strong skills in Python or Go, modern C# and Microservices. As part of their team, you’ll work on developing an entity resolution system within a cloud-first, microservices environment.
Key Responsibilities
Develop and deploy serverless applications using Python or Go
Build secure and efficient backend systems
Collaborate closely with frontend developers and product managers to create seamless user experiences.
Write excellent unit tests
Refactor existing code base
Requirements
Strong experience with Python and/or Go
Strong experience with C#
Excellent working experience within a Microservices environment
Excellent working experience with cloud infrastructure
Competitive daily rate
Hybrid Working – 2 days p/w onsite. Central London
Contract position, outside IR35
If you are interested in finding out more about this hire please reach out to bradley@enigma-rec.ai for immediate consideration.
Contract Senior Software Developer – Python, Go, C#, AWS & Microservices – Contract Software Developer
London, United Kingdom
On site
08-01-2025
- Company Name
- Enigma
- Job Title
- Contract Geohazard Scientist | Earth Science | Geology | Python | Machine Learning
- Job Description
-
Contract Geohazard Scientist - Earth Science, Geology, Python, Machine Learning
About the role
We are looking for a skilled scientist on a contract basis with expertise in geophysics or remote sensing hazard modelling to join our team. In this role, you'll contribute to the development and expansion of our in-house landslide and subsidence risk models, helping to extend their application to new geographic regions. As part of a collaborative, multi-disciplinary Science Team, you'll work alongside experts in climate science, machine learning, and natural hazard modelling. This position is well-suited to someone experienced in working with large, complex geospatial datasets, with a proven track record of training and validating machine learning models for production use. If you're excited about applying your skills to advance cutting-edge hazard modelling, we'd love to hear from you.
The impact you'll own
Geohazards model development and implementation: You'll be spearheading the research and implementation of our existing geo hazard machine learning models as we expand into new regions. You'll be tasked with acquiring training and validation data for these models from diverse open-source data sources.
Fine-tune and future-proof our models: Take ownership of calibrating and validating models to meet the highest scientific, practical, and regulatory standards. You'll ensure these models perform seamlessly at a continental scale, empowering clients with useful and reliable risk assessments.
Bring creativity to validation challenges: Use your hazard modelling expertise to tackle qualitative validation in innovative ways, especially when data is scarce. Your insights will help us push boundaries and improve outcomes.
Lead with vision and expertise: Showcase your technical prowess by documenting and presenting models for scientific peer review. Collaborate with stakeholders to shape the future of our geohazard solutions and drive innovation at every step. A key output of your work will be technical and qualitative validation reports of your model for regulatory purposes.
Essential Skills
Solid understanding of geophysical processes, especially subsidence and landslides, with the ability to apply this knowledge to model land-based hazards.
Practical experience with supervised machine learning models; i.e., experience of training, calibrating, and validating models on diverse datasets. Applying these models at large geographic scales.
Strong programming skills in geospatial computing and machine learning (geopandas, GDAL, xarray, sklearn, scipy, numpy, QGIS). Skilled in using cloud computing services (e.g. AWS) or similar High-Performance Computing (HPC) environments for data-intensive projects.
Experienced in data sourcing and wrangling of Earth Observation/geospatial data at terabyte scale.
Strong written communication skills with ability to explain complex concepts to a non-technical audience.
Desirable Skills
Experience in any one of these areas makes you stand out but are not required for the role and if you are passionate and interested in the role we encourage you to apply!
Experience building, validating and documenting models within a regulated industry (e.g. financial services industries).
Knowledge of recent literature in geophysical hazard (e.g. volcano, subsidence) monitoring and modelling approaches.
Experience with radar Earth Observation data for Differential Synthetic Aperture Radar Interferometry (DInSAR) of ground motion for subsidence monitoring.
Qualifications
PhD or equivalent experience in geophysics, geological, or environmental sciences disciplines.
Minimum of 3 years of industry experience in (geo)physical hazard modelling or machine learning.
Essential Information
Competitive Daily Rate, outside IR35
Hybrid Working – 3 days p/w onsite. Central London
Contract position
For immediate consideration please send over your most up to date CV to emily@enigma-rec.ai
Contract Geohazard Scientist - Earth Science, Geology, Python, Machine Learning
London, United Kingdom
On site
07-01-2025