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- Tasks: Lead the development of AI systems for scientific workflows using natural language interfaces.
- Company: Join an interdisciplinary team advancing AI-driven biology and scientific discovery.
- 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 technology in a collaborative environment.
- Qualifications: Experience 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 | Hybr... 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 | Hybr...
✨Tip Number 1
Familiarise yourself with the latest advancements in natural language processing and large language models. Being well-versed in current trends and technologies will not only boost your confidence but also help you engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the AI and scientific research fields. Attend relevant meetups, webinars, or conferences to connect with potential colleagues and learn about their experiences. This can provide valuable insights and may even lead to referrals.
✨Tip Number 3
Showcase your hands-on experience with Python and relevant frameworks like PyTorch by working on personal projects or contributing to open-source initiatives. Having a portfolio of practical applications can significantly enhance your credibility.
✨Tip Number 4
Prepare to discuss how you've tackled complex scientific problems in the past. Be ready to share specific examples of workflows you've designed or automated, as this will demonstrate your ability to translate scientific challenges into effective solutions.
We think you need these skills to ace AI Engineer | Natural Language Processing | Large Language Models | LLM | Python | Pytorch | Hybr...
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, API design, and distributed systems. Emphasise any projects or roles where you've worked with LLM orchestration and intelligent information retrieval.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how it intersects with scientific research. Mention specific technologies or frameworks you’ve used, such as LangChain or OpenAI APIs, and how they relate to the role.
Showcase Relevant Projects: Include links to any relevant projects or GitHub repositories that demonstrate your skills in developing autonomous systems or working with natural language processing. This will give the hiring team insight into your practical experience.
Highlight Collaboration Skills: Since the role involves working closely with scientists, mention any past experiences where you collaborated with interdisciplinary teams. Highlight your ability to translate complex technical concepts into understandable terms for non-technical stakeholders.
How to prepare for a job interview at Enigma
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, API design, and distributed systems. Highlight specific projects where you've used LLM orchestration and frameworks like LangChain or LlamaIndex, as this will demonstrate your hands-on expertise.
✨Understand the Role's Impact
Familiarise yourself with how autonomous agents can transform scientific workflows. Be ready to explain how your skills can contribute to developing intelligent systems that enhance research capabilities, showing your alignment with the company's mission.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your ability to architect complex workflows. Practice explaining your thought process in designing multi-step systems using tools like Airflow or Prefect, as this will showcase your problem-solving skills.
✨Demonstrate Collaboration and Curiosity
Since the team values collaboration, be ready to share examples of how you've worked with scientists or cross-functional teams. Discuss your curiosity about scientific challenges and how it drives your work, which aligns with their culture of innovation.
