49 Job openings found

Technical Skills Strong programming experience in Python (mandatory) Hands-on experience with ML/AI frameworks: TensorFlow, PyTorch, Keras, Scikit-learn Knowledge of Machine Learning, Deep Learning, and statistical modeling Experience with NLP (text classification, chatbots, LLMs) or Computer Vision is a plus Data handling using NumPy, Pandas and visualization tools Experience with SQL / NoSQL databases Familiarity with REST APIs ...

Mandatory Skills: Champion the entire ML lifecycle, from data exploration and feature engineering to model selection, training, evaluation, deployment, and maintenance. Experience in developing application using LLM models, Generative AI Experience in using RAG, Fine Tuning LLM models (Llama, Gemma etc) Knowledge of Python, R,  or other AI/ML tools Knowledge AI/ML libraries frameworks like Langchain, Transformers, ...

Position- ML Engineer Role & responsibilities-Requirements and Responsibility? Participate in discovery processes collaborating with key stakeholders to identify businessrequirements and expected outcomes.? Develop Neural Network models for information extraction from mortgage documentsusing Computer Vision and NLP techniques.? Deliver high-quality software based on best practices for data collection, modeling, andsoftware development? Design ...

Description: Role:  AI/ML Developer Education: MCA, BE/B.Tech-IT/Computer, MSC-IT Experience: Minimum 5 years of experience   Responsibilities: Design, develop, and implement advanced AI/ML algorithms and models. Collaborate with cross-functional teams to understand business needs and translate them into technical requirements. Research and explore new AI/ML techniques and technologies. Train and optimize AI/ML models on large datasets. Evaluate and improve the ...

Key Responsibilities: - 1. Model Development: Design, build, and optimize supervised, unsupervised, and deep learning models for various business problems. 2. Data Exploration & Feature Engineering: Clean, transform, and analyze structured and unstructured data; identify significant features. 3. AI Integration: Develop end-to-end AI pipelines and integrate models into production systems ...

Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 3.5 - 7 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product ...

Experience Range: 5 to 12 yrs (min 4 years relevant)   Required Qualifications:     2+ years of machine learning and data science experience   3+ years of experience with Python, classical ML methods and deep learning, including deep learning frameworks such as PyTorch or Tensorflow    2+ years leading projects with solid technical communication skills, including demonstrated technical ...

Job description: Responsibilities: Design, develop, and implement advanced AI/ML algorithms and models. Collaborate with cross-functional teams to understand business needs and translate them into technical requirements. Research and explore new AI/ML techniques and technologies. Train and optimize AI/ML models on large datasets. Evaluate and improve the performance of AI/ML models. ...

Role: Senior AI/ML Developer Education: MCA, BE/B.Tech-IT/Computer, MSC-IT Experience: Minimum 3 years of experience   Responsibilities: Design, develop, and implement advanced AI/ML algorithms and models. Collaborate with cross-functional teams to understand business needs and translate them into technical requirements. Research and explore new AI/ML techniques and technologies. Train and optimize AI/ML models on large datasets. Evaluate and improve ...

- 5-7 years of professional experience in data science, with a proven track record ofdelivering impactful solutions in a business setting.- Strong proficiency in machine learning techniques and algorithms, including supervisedand unsupervised learning, deep learning, and reinforcement learning.- Extensive experience in natural language processing (NLP) techniques and frameworks,such as NLTK, ...