Senior AI/ML Engineer

We are on a mission to unlock impossible AI for all.

Imagine a world in which breakthrough discoveries are commonplace. Here at RAIC Labs, we help organizations transcend data-access and data-quality issues, unleashing the full impact of AI in all fields. Simply put, our technology unlocks previously impossible AI that has the power to change the world.

That’s all well and good, but despite our high-tech profile, we recognize that none of this is possible without our people. Which is why we’re thrilled to be adding a Senior AI/ML Engineer to our AI team. We are seeking a highly skilled Senior ML/AI Engineer with expertise in computer vision and deep learning to join our dynamic team. As a key member of our AI team, you will be responsible for designing, implementing, and optimizing cutting-edge AI solutions. The ideal candidate will have a strong background in both artificial intelligence and object-oriented programming in Python, along with a proven track record of delivering successful AI projects.

Here’s what you’ll be working on:

• Writing efficient, reusable, testable, and scalable code for core components of AI projects
• Understanding and analyzing existing code written to carry out AI-related tasks
• Collaborating closely with AI/ML Engineers and Data Scientists to scope out and design AI software packages
• Conducting various experiments, code debugging, and python development with close attention to detail

A good Machine Learning Engineer at RAIC Labs must have the following skills, knowledge, education, and experience:

• Ph.D. degree with 1-2 years of experience in computer science (Software Engineering, Data Science, or Electrical Engineering or related field) or Master’s degree with 3-4 years of experience or Bachelor's degree with 5+ years of experience
• Strong desire to learn and curiosity towards new technologies
• Strong proficiency in Python especially for working with AI/ML libraries (including libraries such as TensorFlow, PyTorch, scikit-learn)
• understanding of object-oriented programming principles
• Hands-on experience with computer vision libraries such as OpenCV and YOLO for object detection, segmentation, and tracking...
• Strong theoretical and practical knowledge in machine learning, deep learning (CNNs, RNNs, GANS, transformer-based models, etc.), and computer vision algorithms.
• Hands-on experience with hyperparameter tuning, model optimization, and working with large datasets in computer vision.
• Knowledge of traditional algorithms and image processing techniques like edge detection, feature extraction methods, and dimensionality reduction.
• Strong mathematical skills in linear algebra, probability, and statistics as applied to machine learning and computer vision.
• Strong knowledge of Git for version control and collaboration in a team setting (forking, branching, merging)
• Experience building, maintaining, and deploying docker containers to virtual machines
• Familiarity with GPU acceleration using CUDA for optimizing model training and inference.
• Strong collaboration and communication skills, with the ability to work in multidisciplinary teams.

If you want to go above and beyond, bring these skills and characteristics to the table:

• Experience with cloud-based data processing platforms and tools (e.g., AWS, GCP, Azure)
• Implemented state-of-the-art models from research papers
• Solid background in deep learning: layer details, loss functions, accuracy metrics, optimization, etc.
• Experience with frameworks/languages such as JavaScript (for Web-based computer vision applications) or MATLAB can also be beneficial.