4 Π΄Π½Ρ Π½Π°Π·Π°Π΄
Software Engineer (Inference Platform, AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Software Engineer (Inference Platform, AI) (Kubernetes/ML Serving): Develop and operate an inference platform serving fleets of machine learning models to scientific applications with an accent on scalability, reliability, and high-throughput performance. Focus on optimizing distributed inference services, designing cloud-native infrastructure, and supporting larger models and growing data volumes.
Location: London, United Kingdom. Hybrid working requires coming into the office 3 days a week.
Company
applies AI and machine learning to drug discovery, building predictive and generative models based on and beyond AlphaFold to develop innovative medicines.
What you will do
- Develop and operate an inference platform serving fleets of machine learning models to scientific applications.
- Optimize inference services to solve scaling limits and deliver high-throughput performance across the model-serving stack.
- Work with research and applied ML teams to improve infrastructure stability, reliability, and scalability.
- Contribute to tooling and architectural design decisions.
- Deliver high-quality, well-tested, user-focused features.
Requirements
- Hands-on experience deploying and scaling inference frameworks such as KServe or Seldon within Kubernetes.
- Strong understanding of cloud-native machine learning lifecycle management.
- Strong programming skills and a reliability-first approach to software development.
- Experience developing, operating, and debugging large-scale distributed systems and high-throughput architectures.
- Understanding of Infrastructure as Code, CI/CD pipelines, observability, and modern DevOps practices.
- Ability to work from the London office 3 days per week.
Nice to have
- Experience with Google Cloud Platform.
- Familiarity with workload scheduling, ML efficiency research, and hardware benchmarking.
- Experience with GPU-aware infrastructure and specialized inference servers such as Triton or TF Serving.
Culture & Benefits
- Collaborative, interdisciplinary environment spanning drug discovery, research, and applied machine learning.
- Values focused on curiosity, creativity, care, initiative, integrity, determination, and cross-field collaboration.
- Hybrid working model designed to support knowledge sharing and in-person collaboration.
- Commitment to equal employment opportunities and reasonable accommodations for disabilities or additional needs.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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