Senior AI/ML Engineer
14 hours ago
London
About Us: AmpsTek – a global technology leader since 2013 – is transforming how businesses approach technology and staffing solutions. Founded by seasoned technology leaders across the UK, Europe, APAC, North America, and LATAM, and with registered offices in 30+ countries, we deliver exceptional service, scalable solutions, and measurable impact. With a portfolio of 200+ clients and millions of users across web and mobile platforms, we empower businesses to innovate, grow, and succeed. Join our team and be part of a dynamic, growth-oriented organization that values talent, creativity, and results. Role Title: Senior AI/ML Engineer Location : London, UK (Hybrid 3 days onsite/week) Contract (Inside IR35) Key Responsibilities: • 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 DataLake architectures., • Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods)., • Implement deep learning architectures (CNN, RNN, LSTM) using TensorFlow, PyTorch, and Keras., • Work on NLP and Generative AI tasks including embeddings, transformers (BERT, GPT), and OpenAI APIs., • Integrate agentic AI frameworks (LangChain, LangGraph, 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. Required Skills: Analytical Tools: • EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn), • Statistical & Multivariate Analysis Big Data: • Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark, • DataLake 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: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AI • NLTK, CBoW, n-grams, Word2Vec, TF-IDF, 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, tensorflow, 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), LangChain, LangGraph, Bedrock Agents, CrewAI, Helicone