Senior AI​/ML Engineer

Senior AI/ML Engineer

Location:

London
Work mode:
Hybrid, 3 days WFO
Contract duration: 1 year

• Build and optimize AI/ML pipelines for predictive modeling, NLP, and generative AI applications.
• Perform Exploratory Data Analysis (EDA), data mining, and visualization to extract insights.
• Design and implement Big Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures.
• Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods).
• Implement deep learning architectures (CNN, RNN, LSTM) using Tensor Flow, PyTorch, and Keras.
• Work on NLP and Generative AI tasks including embeddings, transformers (BERT, GPT), and OpenAI APIs.
• Integrate agentic AI frameworks (Lang Chain, Lang Graph, MCP, Bedrock Agents) for autonomous workflows.
• Collaborate with cross-functional teams to deploy AI solutions in production environments.
• Ensure scalability, security, and compliance of AI systems.

• Analytical Tools
  : EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn)
• Statistical & Multivariate Analysis

• Big Data
  :
  Hadoop, Map Reduce, HDFS, Data Bricks, Spark, PySpark;
  Data Lake Architecture, AWS Redshift, Kinesis, EMR

• Machine Learning
  • Supervised Models:
    Naïve Bayes, Logistic Regression, SVM, Linear Regression, KNN
  • Tree-Based Models:
    Decision Trees, Random Forest, Gradient Boosted Trees, XGBoost
  • Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering

• Deep Learning
  : ANN, CNN, RNN, LSTM;
  Frameworks:
  Tensor Flow, PyTorch, Keras

• NLP & Generative AI
  • Word Embeddings, Transformers (BERT, ELMo), OpenAI Models: GPT-3.5 Turbo, GPT-4o, GPT-3o Reasoning, text-embedding-ada-002

• Libraries & Tools
  : numpy, pandas, scipy, scikit-learn, tensor flow, keras, nltk, matplotlib, seaborn, plotly

• Programming Languages
  :
  Python, R, C++, C#, Java, Node.js, HTML, SQL

• Agentic AI
  :
  OpenAI Agents SDK, Model Context Protocol (MCP), Lang Chain, Lang Graph, Bedrock Agents, CrewAI, Helicone