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For Companies At a Glance
- Tasks: Lead the development of AI systems for scientific tasks using natural language interfaces.
- Company: Join an interdisciplinary team advancing scientific discovery through generative AI models.
- Benefits: Enjoy competitive pay, private health insurance, flexible work, and inclusive leave policies.
- Why this job: Shape the future of science with cutting-edge AI while collaborating in a dynamic environment.
- Qualifications: Expertise in Python, LLM orchestration, and intelligent information retrieval is essential.
- Other info: We value diversity and encourage applicants from all backgrounds to apply.
The predicted salary is between 43200 - 72000 £ per year.
The Opportunity
We are seeking a highly skilled AI Engineer to lead the development of advanced agentic workflows that transform how scientists interact with our platform. You will design and implement autonomous systems capable of navigating complex scientific tasks—such as retrieving scientific data and designing protein binders—using natural language interfaces. In this role, you will architect and deploy intelligent agents that democratize access to cutting-edge tools in synthetic biology, enabling global researchers to leverage our capabilities through intuitive conversational systems.
About Us
We are an interdisciplinary team developing generative models to advance scientific understanding and discovery. Our team members have previously contributed to major breakthroughs in AI-driven biology, diffusion models, laboratory automation, and large-scale screening technologies. We value curiosity, scientific rigor, and collaboration. With offices in multiple international locations, we support team cohesion through regular offsites and a strong culture of trust and innovation.
We are looking for individuals driven by impact, excited by deep technical challenges, and motivated by the opportunity to shape the future of science and technology.
Who You Are
- Experienced software engineer with expertise in Python, API design, and distributed systems.
- Skilled in LLM orchestration, with hands-on experience using APIs (e.g. OpenAI, Anthropic) and frameworks like LangChain, LlamaIndex, or custom agent platforms.
- Proficient in intelligent information retrieval, including RAG systems, vector databases, and embedding models.
- Capable of architecting complex, multi-step workflows with tools such as Airflow, Prefect, or Temporal.
- Comfortable working at the intersection of science and engineering, with familiarity in libraries like NumPy, SciPy, and pandas, and experience handling academic literature and data formats.
Bonus Qualifications
- Background in academic research or research software engineering.
- Experience in scientific automation, document parsing, OCR, and data extraction from research papers.
- Familiarity with academic or pharmaceutical research workflows.
- Expertise in natural language processing, particularly for scientific texts and citation networks.
Key Responsibilities
- Develop autonomous agents capable of executing complex scientific workflows through natural language.
- Architect end-to-end systems that integrate platform capabilities with decision-making for advanced scientific tasks.
- Build pipelines for autonomous literature mining, disease pathway identification, and target discovery.
- Create agents that support scientific content generation, including hypothesis design and research writing.
- Develop agents for automating experimental design and orchestrating biological system validation.
- Work closely with scientists to translate research challenges into intelligent automation tools.
- Share and publish innovative applications of agentic workflows in science and technology.
What We Offer
Competitive compensation and benefits, including:
- Private health insurance
- Retirement contributions
- Inclusive leave policies (e.g. gender-neutral parental leave)
- Flexible hybrid work setup
- Opportunities for travel
- A dynamic work environment and the chance to help define the future of scientific discovery through the application of next-generation AI systems.
We are committed to building a diverse and inclusive team and encourage applicants from all backgrounds to apply.
AI Engineer | Natural Language Processing | Large Language Models | LLM | Python | Pytorch | Hybrid, employer: Enigma
Contact Detail:
Enigma Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer | Natural Language Processing | Large Language Models | LLM | Python | Pytorch | Hybrid,
✨Tip Number 1
Familiarise yourself with the latest advancements in natural language processing and large language models. Being able to discuss recent breakthroughs or trends during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Showcase your hands-on experience with relevant tools and frameworks like Python, PyTorch, and LangChain. Prepare to discuss specific projects where you've implemented these technologies, as practical examples can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the AI and scientific research community. Attend meetups, webinars, or conferences related to AI engineering and synthetic biology to make connections that could lead to valuable insights or referrals.
✨Tip Number 4
Prepare to articulate how you can bridge the gap between science and engineering. Think of ways you can contribute to the team’s mission of democratizing access to scientific tools, as this aligns closely with our values at StudySmarter.
We think you need these skills to ace AI Engineer | Natural Language Processing | Large Language Models | LLM | Python | Pytorch | Hybrid,
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, LLM orchestration, and any relevant frameworks like LangChain or LlamaIndex. Emphasise your skills in intelligent information retrieval and complex workflow architecture.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and its application in scientific discovery. Mention specific projects or experiences that demonstrate your ability to develop autonomous systems and work at the intersection of science and engineering.
Showcase Relevant Projects: If you have worked on projects involving natural language processing or scientific automation, be sure to include these in your application. Detail your role, the technologies used, and the impact of your work.
Highlight Collaboration Skills: Since the role involves working closely with scientists, emphasise your teamwork and collaboration skills. Provide examples of how you've successfully worked in interdisciplinary teams to solve complex problems.
How to prepare for a job interview at Enigma
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, LLM orchestration, and frameworks like Pytorch. Bring examples of past projects where you've implemented intelligent information retrieval or built complex workflows, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Mission
Familiarise yourself with the company's focus on transforming scientific workflows through AI. Be ready to articulate how your skills can contribute to their goals, especially in developing autonomous agents for scientific tasks.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Practice solving problems related to natural language processing and scientific automation, as this will showcase your ability to think critically and apply your knowledge in real-world scenarios.
✨Demonstrate Collaboration Skills
Since the role involves working closely with scientists, highlight your experience in interdisciplinary teams. Share examples of how you've successfully collaborated with others to translate complex challenges into effective solutions.
