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Job Title: AI/ML Engineer - GCP
Location: UK - Remote
Duration: 6 Months (Extendable)
Employment Type: Contract B2B/Freelance {Inside IR35}
Roles & Responsibilities:
About the Role
We are seeking an experienced AI/ML Engineer to help enterprise clients accelerate their adoption of advanced machine learning technologies. This role will focus on building graph-based neural network (GNN) models, generating ScaNN-based embeddings, and training scalable ML models for search, recommendation, and classification systems. You will collaborate closely with Google Cloud engineers, architects, and data scientists to deliver innovative, production-ready AI solutions.
Key Responsibilities
- Design and implement Graph Neural Network (GNN) architectures for enterprise-scale applications.
- Develop and optimize vector embedding generation pipelines using ScaNN or similar ANN techniques.
- Train, fine-tune, and deploy ML/DL models using TensorFlow, PyTorch, JAX, or similar frameworks.
- Collaborate with data engineers and solution architects to integrate models into scalable cloud solutions.
- Perform model evaluations, A/B testing, and hyperparameter tuning for optimal performance.
- Build reusable pipelines and tools for ML training, deployment, and monitoring on GCP.
- Engage directly with customer technical teams to understand business needs and translate them into ML solutions.
- Produce technical documentation and presentations for internal and customer-facing stakeholders.
Required Qualifications
- Bachelor’s degree in computer science, Mathematics or a related technical field or equivalent practical experience.
- Certifications Minimum: Google Professional Data Engineer Preferred: AWS Machine Learning Specialty Certification
- 7+ years in a customer facing role working with enterprise clients
- 4+ years of experience working in enterprise data warehouse and analytics technologies Hands-on experience building and training machine learning models.
- Experience writing software in one or more languages such as Python, Scala, R, or similar with strong competencies in data structures, algorithms, and software design.
- Experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano).
- Strong coding skills in Python and familiarity with ML/DL libraries like TensorFlow, PyTorch, or JAX.
- Knowledge of data analytics concepts, including data warehouse technical architectures, ETL and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
- Customer facing experience of discovery, assessment, execution, and operations. Demonstrated excellent communication, presentation, and problem solving skills.
- Experience in project governance and enterprise customer management.
- Proficiency in building Graph Neural Networks (GNNs) using frameworks like DGL, PyTorch Geometric, or similar.
- Experience with ScaNN or other approximate nearest neighbor (ANN) techniques for vector similarity search.
- Hands-on experience with Google Cloud Platform (GCP) tools such as Vertex AI, BigQuery, and Dataflow.
- Strong problem-solving and communication skills, including the ability to work with clients and cross-functional teams.
Preferred Qualifications
- PhD in Computer Science, AI/ML, or related field.
- Experience with production ML systems and MLOps pipelines using Kubeflow or Vertex AI Pipelines.
- Knowledge of transformers and large language models (LLMs).
- Understanding of recommender systems, natural language processing, or graph-based search engines.
- Contributions to open-source ML libraries or published research in AI/ML.
