AI Engineer

Summary

Results-driven AI and Machine Learning Engineer with 10+ years of experience architecting, training, and deploying scalable machine learning systems across [industry/domain, e.g., fintech, healthcare, e-commerce, autonomous systems]. Expertise spans NLP, computer vision, time-series forecasting, generative AI, MLOps with deep proficiency in Python, PyTorch/TensorFlow, distributed computing, and cloud-native deployment (AWS/GCP/Azure). Successfully delivered [number] production-grade AI solutions that [quantified impact, e.g., improved prediction accuracy, reduced inference latency by 90%, automated 1hr hours of manual workflows, or generated $M in cost savings/revenue. Recognized for bridging cutting-edge research with robust engineering practices, including designing CI/CD pipelines for ML, implementing real-time model monitoring, and leading cross-functional teams to ship reliable, scalable models. Committed to building ethical, maintainable, and high-impact AI systems that align technical innovation with measurable business outcomes.

Expectations

Production Machine Learning Engineer with 6+ years building, deploying, and operating scalable AI systems at the intersection of computer vision, video analytics, and LLM-powered agentic workflows. Expert in Python with strong software engineering foundations: type-safe code, comprehensive testing, CI/CD, containerization, and production API design. Proven track record of shipping object detection/tracking pipelines for full-motion video, self-hosting open-source LLMs via vLLM/Hugging Face, and integrating agentic capabilities into production applications. Comfortable transitioning codebases to Go, optimizing inference latency/throughput, and establishing MLOps standards. Focused on real software delivery, measurable system reliability, and production-grade AI that scales under load.

Employment Preferences

Expected Base Salary

**0,000 USD

Expected Total Compensation

**0,000 USD

Expected Hourly Rate

** USD/hr

Academic Degree

Security Clearance Level

Experience

Skills

• Languages
• SE Practices
• Python
• Expert
• Go
• Proficient
• Transitioning
• C++
• FastAPI
• GRPC
• Pytest
• Mypy
• Ruff
• Pre-commit
• CI
• CD
• GitHub Actions
• GitLab
• Docker
• Kubernetes
• OpenTelemetry
• Structured Logging
• Computer Vision
• Video
• Object Detection
• YOLO
• Detectron2
• RT-DETR
• Object Tracking
• ByteTrack
• DeepSORT
• OC-SORT
• Full-Motion Video Pipelines
• GStreamer
• FFmpeg
• RTSP
• Visual Embeddings
• Similarity
• CLIP
• DINOv2
• Contrastive Learning
• Frame-Level Processing
• MAP
• IDF1 Optimization
• LLMs
• Agentic Systems
• VLLM
• Hugging Face Transformers
• Open-Source LLMs
• Llama 3
• Mistral
• Qwen
• Self-Hosting
• Quantization
• AWQ
• GGUF
• Agentic Workflows
• LangGraph
• AutoGen
• Tool
• Function Calling
• RAG
• Prompt Versioning
• Structured Output Generation
• MLOps
• Infrastructure
• Helm
• Terraform
• MLflow
• Weights
• Biases
• Model Serving
• Triton
• TGI
• Vector DBs
• Milvus
• Weaviate
• Prometheus
• Grafana
• Canary
• Blue-Green Deployments
• SLO
• SLA Management