6 Model Training Jobs

Description We are seeking a Generative AI Trainer to join our dynamic team in India. In this role, you will be responsible for training generative AI models, developing training datasets, and collaborating with teams to enhance AI applications. The ideal candidate will have a solid foundation in machine learning and a passion for advancing AI technologies. Responsibilities Develop and curate training datasets for generative AI models. Assist in the design and implementation of training modules for AI applications. Conduct training sessions for AI models, ensuring adherence to best practices. Collaborate with cross-functional teams to integrate AI solutions into existing systems. Evaluate the performance of generative AI models and suggest improvements. Skills and Qualifications Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 1-3 years of experience in machine learning or AI model training. Strong understanding of natural language processing (NLP) and computer vision concepts. Proficiency in programming languages such as Python, Java, or R. Experience with AI frameworks like TensorFlow, PyTorch, or Keras. Familiarity with data preprocessing techniques and tools. Good analytical and problem-solving skills. Excellent communication and teamwork abilities.

Job Description: We are seeking a skilled and innovative AI/ML Engineer to design, build, and deploy machine learning solutions that solve complex business challenges in mission-critical industries. You will work with multidisciplinary teams to apply AI, ML, and deep learning techniques to large-scale datasets and real-time operational systems. Key Responsibilities: Design and implement end-to-end ML pipelines: data ingestion, model training, evaluation, and deployment Build predictive and prescriptive models using structured, unstructured, and real-time data Develop and fine-tune deep learning models for NLP, computer vision, or time series forecasting Integrate ML models into enterprise platforms, APIs, and dashboards Work closely with domain experts, data engineers, and DevOps teams to ensure production-grade performance Conduct model validation, bias testing, and post-deployment monitoring Document workflows, architecture, and results for reproducibility and audits Research and evaluate new AI tools, techniques, and trends Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or related field 5-7 years of hands-on experience in developing and deploying ML models Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost) Experience with NLP (BERT, spaCy) or CV frameworks (OpenCV, YOLO, MMDetection) Familiarity with data processing tools (Pandas, Dask, Apache Spark) Proficient in SQL and experience with time-series or sensor data Knowledge of ML Ops practices and tools (Docker, MLflow, Airflow, Kubernetes) Industry experience in Oil & Gas, Power Systems, or Urban Analytics Hands-on with edge AI (Jetson, Coral), GPU compute, and model optimization Cloud services: AWS SageMaker, Azure ML, or Google AI Platform Familiarity with REST APIs, OPC-UA integration, or SCADA data sources Knowledge of responsible AI practices (explainability, fairness, privacy).

As a Prompt Engineer , you will play a crucial role in designing and refining the conversational prompts that power our AI voice agents. You will work closely with AI researchers, product managers, and developers

URGENT Freelance Trainer Opportunity: NVIDIA-Certified Trainer for Advanced Programming Course (1 Week) We are seeking NVIDIA-certified trainer to deliver a week-long, in-depth classroom class room training session on advanced programming for NVIDIA DGX systems. The training will focus on the following key areas: Training Topics: Docker Containers : Introduction to the concept and practical use for model deployment and environment management. Model Training : Deep dive into model training techniques and workflows using NVIDIA DGX systems. GPU Memory Distribution & ONNX : Understanding GPU memory management and how ONNX facilitates cross-platform model deployment. TensorRT & Triton : Concepts behind TensorRT for model inference optimization, and using Triton for model serving and deployment. Hands-on Lab : Practical exercises on implementing TensorRT and Triton in real-world scenarios. Advanced Optimization Techniques : In-depth strategies for optimizing deep learning models on GPUs for performance improvements. Future Trends in GPU Computing : Exploration of the latest advancements and future directions in GPU-based computing, AI, and machine learning. Requirements: Must be an NVIDIA-certified trainer with proven expertise in advanced GPU programming. Availability to conduct a full one-week training course (5 days). Strong hands-on experience with NVIDIA DGX , Docker , TensorRT , Triton , and ONNX . Ability to deliver both conceptual learning and practical lab sessions effectively. If you have the required expertise and are available for this one-week on-site session engagement, please reach out with your credentials and relevant experience. Mail ID : Sapna.raturi@softelnetworks.com

Total AI Systems, Inc., headquartered in Lansing, Michigan, specializes in developing commercial software solutions that utilize advanced artificial intelligence to improve business efficiency. We are a profitable, product-based company with offices in the United States, India, and Canada. Our team is made up of rockstars who know that delivering a rockstar performance for our customers means going above and beyond. Whether its early mornings, late nights, or continuous practice and refinement, we are dedicated to providing our very best and having a lot of fun along the way. We take care of our employees, and in turn, they take care of us. We're seeking individuals who are ready to go the extra mile and join us on this journey! We are currently seeking AL/ML Engineers to join our dynamic team. The ideal candidate will possess deep technical expertise in machine learning and artificial intelligence, with a proven track record of developing scalable AI solutions. Your role will involve everything from data analysis and model building to integration and deployment, ensuring our AI initiatives drive substantial business impact. The following are some of the responsibilities for this position: Develop end-to-end AI/ML solutions with a strong focus on GenAI, NLP and predictive analytics. Identifying problems in the current product and working in tandem with AI and backend engineers or the implementation of the solutions to these problems and train/optimize/validate models for all the identified ML/AI/NLP/CV/GenAI problems. Experience delivering and maintaining productionized end-to-end Machine Learning solutions, form data preparation, experimentation, model training, model serving and model update. Design, train, and deploy ML models to production environments. Collaborate with developers, designers and product managers to build scalable and effective solutions. Write clean, maintainable and efficient code in Python and Node.js. Work with various databases (SQL, NoSQL, RDB, etc.) and ensure data integrity. Design and develop backend logic to support ML applications. Leverage cloud platforms (preferably AWS) for deploying and managing AI solutions. Use Docker to containerize applications for streamlined deployment. Continuously explore and integrate new ML tools, frameworks and best practices. This is an exciting position with a growing company and offers a lot of upsides. This is a challenging position that requires dedication and determination. Some requirements of the position include: 1-3 years of experience in machine learning engineering or AI, preferably in a SaaS environment. Hands on experience in NLP and generative AI models, with a solid foundation in Python, node js and exposure in model fine-tuning and training. Experience working in a small, product-based company with a hands-on approach. Proven track record of building and delivering software products in a small team environment. Solid understanding of databases (SQL, NoSQL, Relational Database, Low-code, No-code) and data modeling. Experience deploying ML models and services in production environments. Should have experience with NLP, GenAI technologies and cloud platforms (AWS preferred). Working knowledge of Docker for application deployment. Strong software engineering skills with an interest in end-to-end development. Passion for learning and exploring new technologies. Good to have familiarity with PHP.

Full-Stack AI Developer Generative AI Lead AI app development, from front-end (React/Vue.js) to back-end (REST APIs, cloud). Train & deploy LLMs using TensorFlow/PyTorch.Strong Python, ML, and NLP expertise required. 5+ yrs full-stack, 2+ yrs AI exp.