4 Palm Jobs

The ideal candidate for this position will be responsible for understanding business problems and formulating analytical solutions. You will apply machine learning, data mining, and text mining techniques to develop scalable solutions for various business challenges. You will also be involved in speech to text translation for Video/Audio NLP Analysis and generative AI application for Market Research data. Additionally, you will solve problems using advanced AI techniques, including GenAI methods, by designing NLP/LLM/GenAI applications/products with robust coding practices. Experience in LLM models like PaLM, GPT4, and Mistral is preferred. You will be expected to train, tune, validate, and monitor predictive models, as well as analyze and extract relevant information from large amounts of historical business data in structured and unstructured formats. Furthermore, you will establish scalable, efficient, automated processes for large-scale data analyses and develop and deploy Data Science models on cloud platforms like GCP, Azure, and AWS. Working with large, complex data sets using tools such as SQL, Google Cloud Services, Hadoop, Alteryx, and Python will be part of your daily responsibilities. Preferred qualifications for this role include 2+ years of experience in market research, data mining, statistical analysis, Gen AI, modeling, deep learning, optimization, or similar analytics. Additionally, having 2+ years of work experience with Python, SQL, and/or visualization/dashboard tools like Tableau, PowerBI, or Qliksense is desired. Comfort with working in an environment where problems are not always well-defined and the ability to effectively advocate technical solutions to various audiences are also important. Candidates with 3-4 years of industry experience and a Bachelor's or Master's degree in a quantitative field such as Statistics, Computer Science, Economics, Mathematics, Data Science, or Operations Research are required for this position. You should have 3+ years of experience using SQL for acquiring and transforming data, as well as experience with real-world data, data cleaning, data collection, or other data wrangling challenges. Knowledge in fundamental text data processing and excellent problem-solving, communication, and data presentation skills are essential. Moreover, you should be flexible to work on multiple projects/domains/tools, possess collaborative skills to work with business teams, and be comfortable coding in Tensorflow and/or Pytorch, Numpy, and Pandas, Scikit-learn. Experience with open-source NLP modules like SpaCy, HuggingFace, TorchText, fastai.text, and others is beneficial. Proven quantitative modeling and statistical analysis skills, along with a proactive and inquisitive attitude towards learning new tools and techniques, are highly valued.,

Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets. Immediate Joiners.

Job Summary: We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments. This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies. Key Responsibilities: Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks. Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines. Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks. Optimize model performance, latency, and cost for production use. Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features. Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers. Ensure ethical, secure, and responsible use of AI technologies in all implementations. Required Skills & Experience: 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies. Strong programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc. Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools. Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models. Experience in API development and integration of LLMs into user-facing applications. Preferred Qualifications: Masters or PhD in Computer Science, AI/ML, Data Science, or related field. Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3). Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques. Contributions to open-source AI projects or publications in GenAI/LLM.

Should lead key initiatives in GenAI COE on new tech trends, R and D on new product POC Work on proposals, Provide solutions architecture design solution on different business use cases Ability to work across various different GenAI Models and cloud providers Should have a strong experience in implementing projects in Digital Engineering Or Data Analytics Technically lead a team of developers and groom talent Extensive implementation experience in data analytics space or a senior developer role in one of the modern technology stack Excellent programming skills and proficiency in at least one of the major programming scripting languages used in Gen AI orchestration such as Python or PySpark or Java Ability to build API based scalable solutions and debug & troubleshoot software or design issues Hands on exposure to integrating atleast one of the popular LLMs(Open AI GPT, PaLM 2, Dolly, Claude 2, Cohere etc.) using API endpoints. Thorough understanding of prompt engineering; implementation exposure to LLM agents like LangChain & vector databases Pinecone or Chroma or FAISS Basic data engineering skills to load structured & unstructured data from source systems to target data stores. Build and maintain data pipelines and infrastructure to support Hands on exposure to using cloud(Azure/GCP/AWS) services for storage, serverless-logic, search, transcription and chat Extensive experience with data engineering and should be hands on in using Agentic AI Framework, RAG