Activate Group Limited is looking for a Senior Software Developer to join our development team. In this role, you will apply your expertise in AI/ML and Python to build, deploy, and maintain robust AI-powered solutions at scale. You will combine strong software engineering fundamentals with machine learning engineering skills to deliver production-ready systems.

What You'll Do

Design, develop, and deploy machine learning models and pipelines using Python.
Build and maintain end-to-end ML systems from data ingestion to model serving.
Implement deep learning solutions using PyTorch and TensorFlow.
Develop and optimize NLP solutions and computer vision applications.
Create scalable feature engineering and data preprocessing pipelines.
Build model training, evaluation, and monitoring frameworks.
Implement MLOps practices for continuous model improvement.
Design and maintain vector databases for similarity search and RAG applications.
Integrate LLMs and foundation models into production applications.
Optimize model inference for latency and throughput requirements.
Write clean, efficient, and maintainable Python code following best practices.
Build RESTful APIs and microservices for ML model serving.
Develop data processing pipelines using Apache Spark and Airflow.
Implement real-time streaming solutions for ML features.
Design and optimize database solutions for ML workloads.
Build monitoring and observability solutions for ML systems.
Contribute to system architecture and infrastructure decisions.
Implement comprehensive testing strategies for ML applications.

What We're Looking For

5-8+ years of software development with 3+ years focused on ML/AI.
Bachelor’s degree in Computer Science, Machine Learning, or a related field.
Expert level Python with 5+ years of production experience.
3+ years experience with Machine Learning Frameworks: PyTorch and/or TensorFlow.
Strong proficiency with ML Libraries: scikit-learn, XGBoost, LightGBM.
Expert level Data Processing: pandas, NumPy, Spark.
Practical experience with Deep Learning: CNNs, RNNs, Transformers.
Git proficiency with focus on ML workflows.
Experience with LLMs (GPT, Claude, Llama) and prompt engineering.
Experience with Vector databases (Pinecone, Weaviate, Chroma, or similar).
RAG (Retrieval Augmented Generation) implementation experience.
Experience with Computer Vision libraries (OpenCV, PIL, torchvision).
Experience with NLP libraries (spaCy, NLTK, Hugging Face Transformers).
Experience with model optimization techniques (quantization, pruning, distillation).
Experience with A/B testing for ML models.
Experience with feature stores and data versioning.
Experience with Container technologies: Docker and Kubernetes for ML workloads.
Experience with ML platforms: MLflow, Kubeflow, or similar.
Experience with Cloud ML services: AWS SageMaker, Azure ML, or GCP Vertex AI.
Experience with Model serving frameworks: TorchServe, TensorFlow Serving, FastAPI.
Distributed training experience (Horovod, DDP).
GPU optimization and CUDA programming basics.
Experience with Monitoring tools: Weights & Biases, Neptune, or similar.
Experience with Data pipeline orchestration: Airflow, Dagster, or Prefect.
Experience with Database systems: PostgreSQL, MongoDB, Redis.
Experience with Message queues: Kafka, RabbitMQ for ML pipelines.
Experience with RESTful API and gRPC development.
Experience with Microservices architecture for ML systems.
Data engineering fundamentals.
Security best practices for AI systems.
Performance optimization for inference.
Ability to explain complex ML concepts to non-technical stakeholders.
Experience working with cross-functional teams including data scientists.
Strong analytical skills for debugging ML systems.
Ability to read and implement academic papers.
Track record of applying cutting-edge AI techniques.
Experience deploying ML models in production environments.
Agile/Scrum experience with ML projects.
Familiar with experiment tracking and reproducibility.
Experience with iterative model development.
Focus on continuous learning and improvement.

Nice to Have

Master’s/PhD preferred.
Published research papers or patents in ML/AI.
Contributions to open-source ML projects.
Experience with edge deployment and model optimization.
Knowledge of reinforcement learning.
Experience with multi-modal models.
Familiarity with ethical AI and bias mitigation.
Cloud certifications in ML/AI services.

Technical Stack

Languages & Frameworks: Python, PyTorch, TensorFlow, scikit-learn, XGBoost, LightGBM, pandas, NumPy, Spark, FastAPI, gRPC.
AI/ML Specialized: LLMs (GPT, Claude, Llama), Vector databases (Pinecone, Weaviate, Chroma), RAG, OpenCV, PIL, torchvision, spaCy, NLTK, Hugging Face Transformers.
Infrastructure & Platforms: Docker, Kubernetes, MLflow, Kubeflow, AWS SageMaker, Azure ML, GCP Vertex AI.
Serving & Training: TorchServe, TensorFlow Serving, Horovod, DDP.
Monitoring & Tools: Weights & Biases, Neptune, Airflow, Dagster, Prefect.
Data & Messaging: PostgreSQL, MongoDB, Redis, Kafka, RabbitMQ.

Benefits & Compensation

33 days holiday (including bank holidays).
Personal health cash plan – claim back the cost of things like dentist and optical check ups.
Enhanced maternity / paternity / adoption / shared parental pay.
Life assurance: three times basic salary.
Free breakfasts and fruit.
Birthday surprise for everybody.