Direct message the job poster from CCS Global Tech Talent Acquisition Lead at Helm360-CCS Global Tech About the Company - We are seeking a highly skilled and experienced Machine Learning and GenAI Engineer with strong expertise in cloud platforms, programming, and AI frameworks. The ideal candidate will have a deep understanding of both traditional machine learning techniques and the latest advancements in generative AI (GenAI), as well as the ability to deploy these models into production environments. About the Role - Key Responsibilities: Cloud Platforms: Hands-on experience with major cloud platforms such as Azure, AWS, and Google Cloud, including their AI and machine learning services. Programming: Proficiency in programming languages and frameworks like Python, Java, C#, .NET. Machine Learning and GenAI: Strong knowledge of machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, SciPy, NumPy, and Pandas. Experience working with GenAI models and libraries, such as Hugging Face Transformers, LangChain, OpenAI (GPT, BERT), and other large language models. NLP and GenAI Techniques: Expertise in natural language processing (NLP) techniques such as text preprocessing, tokenization, named entity recognition (NER), sentiment analysis, text classification, topic analysis, and language generation. Experience with fine-tuning pre-trained models for specialized tasks. Traditional Machine Learning Techniques: Familiarity with supervised and unsupervised learning, regression, classification, clustering, ensemble methods, model evaluation, and hyperparameter tuning. Data Storage and Processing: Experience with Databricks, SQL, and NoSQL databases. Scripting: Proficiency with scripting languages like Powershell and Bash. Data Science: Expertise in data preprocessing, feature engineering, statistical analysis, and data visualization. MLOps: Basic understanding of CI/CD tools (e.g., Azure DevOps, Jenkins), containerization (e.g., Docker, Kubernetes), and version control (e.g., Git). Monitoring/Logging: Experience with monitoring and logging tools like Prometheus, Grafana, and Azure Monitor. Core Functions : Stakeholder Collaboration: Work closely with stakeholders, data scientists, and cross-functional teams to gather requirements, align machine learning and GenAI projects with business objectives, and provide technical guidance to non-technical stakeholders. System Integration: Develop AI solutions that integrate with existing enterprise systems, databases, and APIs to ensure smooth data flow and system interoperability. Model Development: Design and fine-tune traditional machine learning models and large language models (LLMs) like GPT, BERT, and others, ensuring optimal performance. NLP Techniques: Apply advanced NLP and GenAI techniques, including text preprocessing, NER, sentiment analysis, and language generation, for specialized business applications. Machine Learning Techniques: Implement and optimize traditional machine learning methods such as classification, regression, and clustering, ensuring high model accuracy. Risk Management: Identify risks related to data privacy, security, and bias, and develop strategies to mitigate these risks, ensuring compliance and ethical AI practices. Continuous Improvement: Continuously assess and enhance machine learning models to improve accuracy and scalability while staying up to date with the latest advancements. Data Pipeline Development: Design and maintain data pipelines for sourcing and processing datasets, ensuring high data quality for training ML and GenAI models. Model Deployment: Deploy machine learning and GenAI models into production using platforms like Azure Machine Learning Studio and Kubernetes. Inference Pipeline Design: Architect low-latency, high-throughput inference pipelines to support both traditional ML and GenAI models in real-time applications. Seniority level Mid-Senior level Employment type Contract Job function Information Technology Industries IT Services and IT Consulting #J-18808-Ljbffr