Bangalore, Karnataka, India
Social Good & Community Development
Full-Time
Dicetek LLC
Overview
We are in need of 1 AI and Machine Learning Engineer who will assist our Team in Emerging Technologies.
The chosen resource needs to work offshore and below are the detailed requirement for this role.
Must Have
The chosen resource needs to work offshore and below are the detailed requirement for this role.
Must Have
- 2 + years in MLOps, DevOps or backend engineering for AI workloads
- DeepStream 7.x poweruser—pipelines, Gstplugins, nvdsanalytics, nvstreammux
- Solid grasp of containerization (Docker) & GPU scheduling
- Proven track record squeezing latency/throughput on NVIDIA GPUs (TensorRT, mixed precision, CUDA toolkit)
- Handson deploying YOLO or comparable CNNs in production
- Experience selfhosting and serving LLMs (vLLM, TensorRTLLM, or similar) plus quantization/pruning/distillation
- Strong Python & bash; confidence with CI/CD scripting
- Exposure to cloud GPUs (AWS /GCP /Azure)
- Experience with edge devices (Jetson, Xavier, Orin)
- Performance profiling with Nsight Systems / DCGM
- Knowledge of Triton Inference Server internals
- Familiarity with distributed training (PyTorch DDP, DeepSpeed)
- Basic frontend/REST gRPC API design skills
- Build & automate inference pipelines
- Design, containerize and deploy CV models (YOLO v8 / v11, custom CNNs) with DeepStream 7.x, optimizing for lowest latency and highest throughput on NVIDIA GPUs.
- Migrate existing Triton workloads to DeepStream with minimal downtime.
- Serve and optimize large language models
- Selfhost Llama 3.2, Llama 4, and future LLM/VLMs on the cluster using bestpractice quantization, pruning and distillation techniques.
- Expose fast, reliable APIs and monitoring for downstream teams.
- Continuous delivery & observability
- Automate build/test/release steps and set up health metrics, logs and alerts so models stay stable in production.
- Allocate GPU resources efficiently across CV and LLM services.
- Model lifecycle support (10 – 20 %)
- Assist data scientists with occasional finetuning or retraining runs and package models for production.
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