3 Multitask Learning Jobs

You should have a minimum of 4+ years of experience in AI-based application development. Your responsibilities will include fine-tuning pre-existing models to improve performance and accuracy. You should have experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks, as well as familiarity with APIs like OpenAI or Vertex AI. Additionally, experience with NLP tools and libraries like NLTK, SpaCy, GPT, and BERT is required. You will be implementing frameworks like LangChain, Anthropics Constitutional AI, OpenAI, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications. Evaluating and analyzing RAG solutions and utilizing the best-in-class LLM to define customer experience solutions will be part of your role. Architecting and developing advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others is also expected. You should have a strong understanding and experience with open-source multimodal LLM models to customize and create solutions. Exploring and implementing cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning is essential. Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib is crucial for this role. Optimizing model performance through experimentation, hyperparameter tuning, and advanced optimization techniques is required. Proficiency in Python with the ability to get hands-on with coding at a deep level is a must. You will also be developing and maintaining APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems. Having the ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational databases (e.g., MongoDB or Cassandra) is necessary. Enthusiasm for continuous learning and professional development in AI and related technologies is highly valued. Collaboration with cross-functional teams to understand business requirements and translate them into technical solutions is expected. Knowledge of cloud services like AWS, Google Cloud, or Azure is necessary. Proficiency with version control systems, especially Git, is required. Familiarity with data pre-processing techniques and pipeline development for AI model training is essential. Experience with deploying models using Docker, Kubernetes, AWS Bedrock, and Sagemaker is a plus. Strong problem-solving skills with the ability to translate complex business problems into AI solutions are crucial for success in this role.,

Are you ready to experiment, learn, and implement in the field of ML, Python, Computer Vision, hardware platforms like Jetson Nano and Raspberry Pi, and cloud services Join us on a new adventure where your expertise can revolutionize the dynamics of our organization. We believe in selection, not rejection, and we are excited to welcome you to our team. OptiSol is your destination for a stress-free and balanced lifestyle. We provide a nurturing environment where your career can flourish. As a certified GREAT PLACE TO WORK for 4 consecutive years, we value open communication, accessible leadership, diversity, and work-life balance with flexible policies. At OptiSol, you can thrive both personally and professionally. We are at the forefront of AI and innovation, shaping the future together. Join us on this journey of learning and growth. What we like to see in you: - Core Competencies: Programming, AI Expertise, IoT Hardware, Protocols (RTSP, TCP, MQTT, Modbus, UART), Leadership - Bachelor's/masters in computer science, ECE, or related fields - Expertise in Python and relevant ML frameworks (TensorFlow, PyTorch, OpenCV) - Strong understanding of neural networks, transfer learning, and optimization techniques - Proficiency with Jetson Nano, Raspberry Pi, Arduino, and related platforms - Familiarity with RTSP, TCP, MQTT, Modbus, UART - Proven experience in leading technical teams and managing projects What do we expect: - Hands-on experience with model quantization, multitask learning, and zero-shot fine-tuning - Familiarity with OCR and multimodal LLMs for different data types - Experience in API development using FastAPI and Django, plus Android AI apps - Knowledge of industrial cameras, motor drivers, and Ethernet switches - Proficiency in CUDA programming and GPU optimization What You'll Bring to the Table: - Lead a team of AI engineers and promote a creative and collaborative environment - Work with stakeholders to define project goals and milestones - Deliver high-quality AI-driven solutions on time - Tweak machine learning and computer vision algorithms for tasks like object detection - Deploy AI on edge devices like Jetson Nano or Raspberry Pi - Integrate AI models with electronics and solve hardware-software challenges - Manage AI services on cloud platforms (AWS, Azure, Google Cloud) - Test, validate, and document solutions following industry best practices Core benefits you'll gain: - Lead and inspire a team of engineers in a collaborative setting - Directly shape project goals and ensure project success - Gain hands-on experience in cutting-edge AI and computer vision applications - Dive into edge devices like Jetson Nano and Raspberry Pi - Manage AI services on cloud platforms securely and efficiently - Develop a well-rounded skill set in AI and hardware Join us as an OptiSolite and discover a fulfilling career with us. Explore life at OptiSol and learn more about our culture on our Insta Page.,

You should have a B.Tech, M.Tech, or higher degree in Computer Engineering, Computer Science, Electronics, Robotics Engineering, or related fields. Your written and verbal communication skills should be strong, and you should possess excellent problem-solving abilities. Proficiency in C++ for robotics and machine perception, along with knowledge in data structures and algorithms, is required. Extensive experience with OpenCV, PCL, and ROS2 is essential. You should be well-versed in Modern C++ with a deep understanding of features like RAII, STL, templates, etc. Experience in implementing Deep Learning Algorithms on GPU cluster for tasks like object detection and segmentation is necessary. Familiarity with Unix/Linux environments is a must, and you should be capable of developing software for real-time processing of sensor data from cameras, LIDAR, and other sensors. Your responsibilities will include building robust solutions to cutting-edge Autonomous driving problems and developing advanced algorithms for tasks like object detection, tracking, multi-task learning, distributed training, and multi-sensor fusion. Experience with developing production-ready software is a plus, along with maintaining large-scale libraries and working with parallel computing libraries like TBB and CUDA. Additional desirable qualifications include familiarity with linear algebra libraries such as Eigen, machine learning, software version management tools like Git, and agile development workflows and CI/CD processes.,