ML- Deep Learning Engineer

Job Title: ML – Deep Learning Engineer

Job Description

This role focuses on designing, developing, and deploying state-of-the-art deep learning solutions with a strong emphasis on 3D computer vision, deep reinforcement learning, and advanced geometric modeling. You will work on complex spatial and geometric problems, build custom neural network architectures and autonomous agents, and take models from research prototypes to scalable production systems. The position is ideal for an engineer with 1 to 4 years of experience who enjoys working from first principles, has a strong mathematical foundation, and is passionate about pushing the boundaries of 3D deep learning and intelligent agents.

Responsibilities

• Lead and contribute to research and development initiatives focused on advanced deep learning models, particularly 3D Convolutional Neural Networks (3D CNNs), deep learning for computer vision, and Deep Reinforcement Learning (DRL) for spatial problem-solving.
• Design and implement custom neural network architectures tailored for 3D data, including models that can interpret, interact with, and generate complex 3D geometries such as CAD data, 3D meshes, point clouds, voxels, and other geometric representations.
• Develop autonomous agents using Deep Reinforcement Learning that can perform complex decision-making tasks in spatial, geometric, or simulated environments.
• Engineer, optimize, and implement core mathematical and algorithmic solutions from first principles, with heavy use of computational geometry, topology, linear algebra, and numerical methods.
• Build proprietary algorithmic pipelines and tools for processing 3D and geometric data natively, rather than relying on off-the-shelf commercial software.
• Train and fine-tune complex models, including DRL agents and 3D CNNs, using modern machine learning frameworks such as PyTorch and TensorFlow in simulated and geometric environments.
• Optimize and scale custom algorithms and large models, including implementing distributed training, parallelism, and leveraging hardware acceleration such as GPUs and TPUs.
• Collaborate closely with engineering teams to integrate 3D deep learning models and agentic workflows into robust, scalable production systems.
• Apply best practices in software engineering, including clean, efficient, and maintainable code in Python and C\+\+, to ensure reliability and performance of deployed models.
• Utilize cloud-based platforms and tools to support scalable model training, distributed computing, and production deployment of AI solutions.

Essential Skills

• 1 to 4 years of hands-on experience developing state-of-the-art deep learning models, with a strong focus on computer vision, 3D CNNs, and advanced deep learning techniques.
• Degree in Computer Science, Applied Mathematics, Artificial Intelligence, or a related discipline, with specialized coursework or research in 3D deep learning, reinforcement learning, and advanced algorithmic design.
• Strong expertise in Deep Reinforcement Learning (DRL) and experience building autonomous agents for complex decision-making tasks in spatial, geometric, or simulated environments.
• Proficiency in deep learning and machine learning algorithms, particularly in the context of 3D vision, reinforcement learning, and generative geometric models.
• Strong programming skills in Python and C\+\+, with the ability to implement complex algorithms and models from scratch.
• Hands-on experience with leading machine learning frameworks such as PyTorch and TensorFlow for training and deploying deep learning models.
• Experience working extensively with 3D data representations, including 3D meshes, point clouds, voxels, and CAD data structures such as B-rep, STEP, and IGES.
• Deep knowledge of core mathematical algorithms, computational geometry, linear algebra, and numerical methods, with a proven ability to design and implement these algorithms.
• Practical experience deploying custom AI models and algorithms at scale in production environments.
• Familiarity with cloud-based solutions and tools (such as AWS, GCP, or Azure) for scalable model training and distributed computing.
• Strong problem-solving skills with a focus on building algorithmic solutions from the ground up and tackling complex spatial and geometric challenges.

Additional Skills \& Qualifications

• Specialized academic or project experience in 3D deep learning, reinforcement learning, and advanced algorithmic design.
• Experience with specialized 3D and geometric processing libraries such as PyTorch3D, Open3D, Trimesh, or similar toolkits.
• Background in topology and advanced geometric modeling concepts applied to spatial data.
• Experience optimizing training pipelines for large-scale models, including distributed and parallel training setups.
• Familiarity with hardware acceleration techniques using GPUs, TPUs, or other specialized accelerators for deep learning workloads.
• Strong interest in research-driven engineering, including reading and implementing ideas from recent academic papers in deep learning and reinforcement learning.
• Ability to collaborate effectively with cross-functional teams, including research, engineering, and product stakeholders.
• Notice period of less than 30 days to enable timely onboarding.

Work Environment

You will work in a highly technical, research-driven engineering environment focused on building advanced deep learning and reinforcement learning solutions for complex 3D and geometric problems. The role involves extensive use of modern machine learning frameworks such as PyTorch and TensorFlow, programming in Python and C\+\+, and working with specialized 3D and geometric libraries like PyTorch3D, Open3D, and Trimesh. You will frequently handle 3D data formats including meshes, point clouds, voxels, and CAD structures such as B-rep, STEP, and IGES. The team leverages cloud-based platforms such as AWS, GCP, or Azure for scalable model training, distributed computing, and production deployment, and makes use of hardware accelerators like GPUs and TPUs to support large-scale experiments. The culture emphasizes innovation, rigorous mathematical thinking, and building proprietary solutions from first principles, offering the opportunity to work on cutting-edge projects in 3D vision, deep reinforcement learning, and autonomous agents in a collaborative and intellectually stimulating setting.

Diversity, Equity \& Inclusion

At Actalent, Diversity And Inclusion Are a Bridge Towards The Equity And Success Of Our People. DE\&I Is Embedded Into Our Culture Through

• Hiring diverse talent
• Maintaining an inclusive environment through persistent self-reflection
• Building a culture of care, engagement, and recognition with clear outcomes
• Ensuring growth opportunities for our people

Actalent is an equal opportunity employer.

About Actalent

Actalent is a global leader in engineering and sciences services. For more than 40 years, we’ve helped visionary companies advance their goals. Headquartered in the United States, our teams span 150 offices across North America, EMEA, and APAC—with four delivery centers in India led by 1,000\+ extraordinary employees who connect their passion with purpose every day.

Our Bangalore, Hyderabad, Pune, and Chennai delivery centers are hubs of engineering expertise, with core capabilities in mechanical and electrical engineering, systems and software, and manufacturing engineering. Our teams deliver work across multiple industries including transportation, consumer and industrial products, and life sciences. We serve more than 4,500 clients, including many Fortune 500 brands. Learn more about how we can work together at actalentservices.com.