Generative AI Engineer
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Crafting the workforce of tomorrow | Generative AI visionaries and AI architects driving excellence at HCL Europe
About the Company: HCLTech is leading India’s IT sector in AI. Last quarter, the company entered into a multi-year partnership with OpenAI, making it the only major Indian IT firm with direct access to ChatGPT’s portfolio.
Since 2016, HCLTech has been developing AI solutions. We have been at the forefront of AI, GenAI and now Agentic AI technologies. We go beyond what’s possible in applying these technologies to drive service transformation and value stream innovation for our clients. Our AI services help enterprises design, develop and deploy AI systems that boost operational efficiency, increase client loyalty, enable new capabilities and open new markets.
With our comprehensive suite of AI services, top-tier partnerships and full-stack capabilities recognized by leading industry analysts, HCLTech is the trusted partner of choice for clients seeking AI solutions that deliver measurable ROI.
About the Role: As a GEN AI Architect, you will play a pivotal role in shaping the design, development, and deployment of advanced Gen AI systems within our organization. This position demands a visionary problem-solver who combines technical expertise with a passion for innovation.
Responsibilities:
- AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the system's scalability, flexibility, and efficiency to handle large algorithms.
- Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy.
- Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training.
- Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights.
- Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency.
- System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules.
- Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage.
- Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities.
- Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences.
Qualifications:
- A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field.
- Experience with large language models (LLMs) and prompt engineering.
- Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks.
- Strong programming skills in languages such as Python, R, or Java.
- Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras.
- Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
- Solid understanding of AI concepts, algorithms, and methodologies.
- Knowledge of designing large scale AI solutions, data integration, cleansing, and transformation techniques.
- Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions.
- Strong communication and collaboration skills to work effectively in multidisciplinary teams.
- Knowledge of ethical AI practices and laws is a plus.
Preferred Skills:
- Knowledge of NVIDIA CUDA, cuDNN, TensorRT.
- Experience with NVIDIA GPU hardware and software stack.
- Understanding of HPC and AI workloads.
- Familiarity with BigData platforms and technologies, such as Hadoop or Spark.
Pay range and compensation package: Competitive salary based on experience and qualifications.
Equal Opportunity Statement: We are committed to diversity and inclusivity in our hiring practices and encourage applications from all qualified individuals.
Seniority level
- Mid-Senior level
Employment type
- Full-time
Job function
- Information Technology
- Industries
- IT Services and IT Consulting, Software Development, and IT System Custom Software Development
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- Location:
- United Kingdom
- Job Type:
- FullTime
- Category:
- IT & Technology