Foundation Model Engineer

5 days ago


Bangalore Karnataka, India ZenteiQ Aitech Innovations Private Limited Full time

As a Foundation Model Engineer at ZenteiQ you will lead the development of large-scale Scientific Foundation Models that integrate deep learning with physical and scientific principles This role blends AI research systems engineering and architectural innovation to create models capable of reasoning prediction and scientific understanding Your work will directly contribute to ZenteiQ s mission to build sovereign ethical and high-performance scientific AI systems that transform industries such as aerospace materials science and energy Key Roles Responsibilities Model Architecture Design and implement scalable foundation model architectures 10B-100B parameters using transformer and hybrid attention mechanisms Distributed Training Build high-efficiency training pipelines with FSDP DeepSpeed and Megatron-LM to optimize multi-node GPU workloads Multimodal Integration Develop cross-modal models combining text image simulation and sensor data for scientific applications Performance Optimization Enhance inference and training performance using quantization KV-cache management mixed precision and CUDA kernel optimization Research and Experimentation Conduct ablation studies evaluate new architectures MoE GQA MQA and publish results in internal and external forums Collaboration Work closely with the data infrastructure and HPC teams to ensure scalable deployment and compliance with security standards Mentorship Guide junior engineers in model design training efficiency and research best practices Project Goals Develop and deploy ZenteiQ s Scientific Foundation Model SFM capable of reasoning over scientific data and equations Achieve breakthroughs in physics-informed deep learning integrating domain constraints with AI-driven learning Advance India s sovereign AI initiative by building a national-scale scientific AI system optimised for precision interpretability and scalability Contribute to open research publications ethical AI practices and reproducible model design frameworks Requirements Required Skills Qualifications Master s or Ph D in Computer Science AI ML or related field Expertise in transformer-based architectures GPT LLaMA T5 etc Proficiency in PyTorch CUDA and distributed training frameworks DeepSpeed FSDP Megatron-LM Experience with HPC environments multi-GPU scaling and parallelization strategies tensor pipeline data Strong understanding of numerical methods scientific computing or physics-informed ML Proven track record in large-model research optimization or deployment Publications or open-source contributions in foundation models preferred Tech Stack PyTorch o CUDA o Flash Attention o DeepSpeed o FSDP o Megatron-LM o JAX o Triton o MoE o RoPE ALiBi o xFormers o HPC o Linux Benefits What We Offer Work on cutting-edge national-scale AI systems Access to H100 H200 GPU clusters and next-gen compute infrastructure Competitive compensation performance bonuses and equity options Opportunity to publish and present at global AI conferences A collaborative ethical and innovation-driven work environment



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