Senior AI ML Engineer in City of London, EN

Senior AI ML Engineer

Location: London, UK, hybrid 3 days a week in office

Role Type: Permanent

Key Responsibilities:

• Design, develop, and deploy AI models tailored to specific project requirements, including Cognitive AI techniques such as NLP, Computer vision, Speech & Conversational AI.
• Good understanding of Document AI development processes, models, and applications.
• Good understanding on working of LLMs. Good to have hands on experience of Generative AI Models & its’ applications.
• Experience delivering and maintaining productionized end-to-end Machine Learning solutions, form data preparation, experimentation, model training, model serving, and model update.
• Utilize MLOps methodologies to streamline the development, deployment, and monitoring of machine learning models.
• Collaborate with data scientists, ML engineers, and other stakeholders to transition prototypes to production.
• Optimize and refine algorithms to improve performance and functionality.
• Ensure integration of AI solutions into cloud platforms such as AWS, Azure, or GCP.
• Stay updated with the latest AI, LLMs, MLOps, and machine learning trends, techniques, and best practices.
• Ensure the robustness, scalability, and reliability of AI solutions.
• Experience in implementing CI/CD pipelines using Azure DevOps/TFS.
• Provide technical leadership and mentorship in AI to other team members.
• Work closely with cross-functional teams to integrate AI solutions into products and services. Requirements:
• At least having 8 to 12 years of experience in AIML
• Proven experience in AI, ML, MLOps, Text Analytics and Generative AI.
• Strong proficiency in programming languages such as Python, Java
• Experience with machine learning frameworks like TensorFlow, PyTorch, Keras, or Scikit-learn.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Experience in Machine Learning and Neural Network architectures like Ensemble Models, SVM, CNN, RNN, Transformers, etc.
• Experience in Natural language processing (NLP) tools: NLTK, Spacy, and Gensim.
• Experience in MLOps tools such as Kubeflow, MLflow, or Azure ML
• Knowledge/hands-on experience with workflow tools like Airflow
• Experience with Microservices architecture
• Experience with SQL and NoSQL databases such as MongoDB, Postgres, Neo4j, etc
• Experienced with RestAPI python frameworks such as Fast API/Flask/Django • Excellent problem-solving skills and a collaborative mindset.
• Strong communication skills to work effectively with diverse teams.

Mandatory Skills

• Bachelor's or master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.
• Experience in querying databases and using statistical computer languages: R, Python etc.
• Published research or contributions to open-source AI/ML projects.
• Experience visualizing/presenting data for stakeholders using: Matplotlib, ggplot, etc.
• Good to have experience with big data platforms and tools like Hadoop, Spark, or Kafka.

Skills to be evaluated on :

• Bachelor's or master’s or PHD in Statistics
• Mathematics
• Computer Science or another quantitative field.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression
• Random Forest Boosting Trees text mining social network analysis etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression R Python etc.
• Published research or contributions to open-source AI/ML projects.
• Experience visualizing/presenting data for stakeholders using: Matplotlib ggplot etc.
• Good to have experience with big data platforms and tools like Hadoop Spark or Kafka.

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