
AI/ML Engineer – Senior Level
2 days ago
Job description
AI/ML Engineer – Senior Level (3+ Years)
Location:
Johar Town, Lahore (On-site)
Type:
Full-time
Company:
Plutus
Overview
Plutus is pioneering AI systems that merge large-scale language understanding, speech intelligence, and blockchain analytics. We're seeking a senior AI/ML engineer who thrives on designing end-to-end, production-grade machine learning solutions, someone who can translate complex research into high-impact features across NLP, ASR, LLM customization, and agentic AI, while pushing the limits of on-chain machine learning.
What You'll Do
- Architect & Own the AI lifecycle:
from raw data ingestion to reproducible training pipelines, evaluation frameworks, and high-availability deployments. - Advance NLP & ASR:
build classification, NER, summarization, RAG, and speech-to-text models that scale to multilingual, noisy real-world data. - Customize frontier LLMs:
apply SFT/LoRA/QLoRA, advanced prompt engineering, and automated evaluation/guardrail strategies to achieve robust, safe outputs. - Engineer agentic AI:
design and implement plan–execute–verify loops, multi-tool function calling, and autonomous workflows capable of reasoning and self-correction. - Optimize inference stacks:
deploy on FastAPI/TGI/vLLM/Triton with tight latency/cost controls, leveraging quantization, caching, and distributed serving. - Instrument intelligence:
create curated datasets, continuous evaluation suites, monitoring dashboards, and drift-detection pipelines for live systems. - Bridge blockchain & ML:
integrate ML models with EVM/Solana data for on-chain analytics, fraud/anomaly scoring, and verifiable/zk-ML proofing.
What We're Looking For
- 3–5 years of applied machine learning with models shipped to production.
- Expert-level Python + PyTorch, with strong Transformer fundamentals and GPU/accelerator optimization experience.
- Hands-on with Hugging Face (datasets, transformers, PEFT/accelerate) and LLM fine-tuning techniques.
- Practical ASR experience (e.g., Whisper) and comfort with multimodal pipelines.
- Strong background in API design and deployment (Docker, CI/CD, FastAPI,Flask) and interpreting live production metrics.
- Ability to distill ambiguous business problems into measurable ML objectives and lead discussions across research, product, and engineering teams.
Bonus Points
Experience with Reinforcement Learning with Human Feedback (RLHF) or Direct Preference Optimization DPO, low-rank adaptation tricks, or aggressive latency tuning.
Blockchain + ML expertise: chain-data analytics, on-chain fraud detection, or verifiable/zk-ML concepts.
Familiarity with distributed training, vector databases (FAISS/pgvector), and advanced observability stacks (Grafana/Prometheus).
Tech Stack
Python, PyTorch, Hugging Face, Whisper, FastAPI, Docker, MLflow/W&B, Redis/Postgres, FAISS/pgvector, TGI/vLLM/Triton, Grafana/Prometheus.
If you have the expertise and ambition to build next-generation AI systems at the intersection of language, speech, and blockchain, send us your CV and portfolio
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