Infoplus Technologies UK Limited
Senior AI/ML Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI/ML Engineer on a contract basis, located in London, UK. Key skills include expertise in AI/ML pipelines, Big Data technologies, deep learning frameworks, and NLP applications. Experience with agentic AI frameworks is essential. Pay rate is "unknown".
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
December 12, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#NumPy #Hadoop #Data Analysis #Predictive Modeling #R #C++ #Keras #Pandas #Matplotlib #Scala #NLP (Natural Language Processing) #Transformers #Regression #C# #PyTorch #Spark (Apache Spark) #Programming #Plotly #Deep Learning #Python #Databricks #ML (Machine Learning) #Compliance #NLTK (Natural Language Toolkit) #HDFS (Hadoop Distributed File System) #"ETL (Extract #Transform #Load)" #Java #SQL (Structured Query Language) #Langchain #Libraries #SciPy #Clustering #Big Data #AI (Artificial Intelligence) #PySpark #Security #TensorFlow #Visualization #BERT #Data Mining #Linear Regression #Redshift #AWS (Amazon Web Services) #RNN (Recurrent Neural Networks) #Logistic Regression #HTML (Hypertext Markup Language)
Role description
Role Title: Senior AI/ML Engineer
Location: London, UK (Hybrid)
Type: Contract Position
Please find below JD:
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
Role Title: Senior AI/ML Engineer
Location: London, UK (Hybrid)
Type: Contract Position
Please find below JD:
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
