AI/ML Developer (5+ Years of Experience)

Location:

About the Role:

Turtleneck Systems and Solutions is looking for a passionate and driven AI/ML Developer to join our growing R&D team. This is an excellent opportunity for recent graduates or early professionals who are eager to apply their skills in deep learning, LLMs, and GPU-based computing to real-world projects.

You’ll be working on cutting-edge technologies involving BERT, LLM-based architectures, CUDA optimization, and model deployment, contributing to scalable AI solutions in NLP, computer vision, and intelligent automation.

Key Responsibilities:

• Architect, design, and deploy scalable machine learning and deep learning solutions.
• Lead the development and fine-tuning of LLMs, BERT, GPT-based models, and transformer architectures.
• Implement, optimize, and profile GPU-accelerated training pipelines using CUDA, PyTorch, and TensorFlow.
• Drive end-to-end ML workflows including data pipelines, preprocessing, experimentation, evaluation, and production deployment.
• Collaborate closely with cross-functional teams to integrate AI solutions into enterprise systems.
• Mentor junior developers and review model architectures, code quality, and deployment strategies.
• Research, experiment, and prototype new AI methodologies to improve system performance and scalability.

Required Qualifications:

• Bachelor’s or Master’s in Computer Science, IT, Electronics, AI/ML, Data Science, or related fields.
• 5+ years of industry experience developing and deploying ML/DL models.
• Deep expertise in Python, PyTorch/TensorFlow, NumPy, Pandas, and scikit-learn.
• Strong experience with CUDA programming, GPU acceleration, and training optimization.
• Hands-on experience with LLMs, transformers, BERT/GPT models, embeddings, and vector search.
• Proven ability to design and scale ML systems in real-world production environments.
• Experience with MLOps tools, CI/CD pipelines, Docker, model versioning, and inference optimization.

Preferred Skills:

• Experience with Hugging Face Transformers, LangChain, & other LLM frameworks.
• Strong understanding of distributed training, model parallelism, quantization, pruning, and low-latency inference.
• Experience building or maintaining RAG systems, semantic search, vector databases, or GenAI applications.
• Familiarity with Kubernetes, cloud platforms (AWS/GCP/Azure), and scalable model serving.
• Research or publications in AI/ML/Deep Learning (nice to have).

What We Offer:

• Work directly with a highly-skilled engineering and research team.
• Freedom to explore and experiment with new AI frameworks and methodologies.
• Flexible work culture with performance-driven career growth.
• A role where your ideas directly shape the company’s core AI products.