MLOps Engineer (Deployment, Monitoring, Model Risk Controls)

DuskByte
Punjab

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Job details

Full-time

Qualifications

CI/CD
Azure
Go
Law
DevOps
Master's degree
Bash (Unix shell)
AWS
Machine learning
Continuous integration
APIs
Data science
AI
Python

Full job description

LLM Lifecycle Management, Model Observability, & AI Safety. Remote / Hybrid · Full-Time

The Mission

The jump from a "Local AI Prototype" to an "Enterprise SaaS Feature" is where most AI projects fail. At DuskByte, we bridge that gap. As an MLOps Engineer, you are the architect of the AI production line. You will ensure that the machine learning models and LLMs we integrate into modernised SaaS platforms are as stable, secure, and observable as the core legacy code we refactor.

What You Will Do (The Role)

Model Deployment Pipelines

Design and maintain automated CI/CD/CT (Continuous Training) pipelines for LLMs and custom ML models using Kubeflow, BentoML, or SageMaker.

AI Observability & Monitoring

Implement real-time tracking for Model Drift, Latency, and Hallucination rates to ensure the AI remains an asset, not a liability.

Model Risk Controls

Build "Guardrail" systems (using NeMo Guardrails or custom logic) to prevent prompt injection, data leakage, and biased outputs.

Vector Database Engineering

Optimize and scale high-performance Vector DBs (Pinecone, Weaviate, or pgvector) to power RAG (Retrieval-Augmented Generation) at enterprise scale.

GPU & Cost Optimization

Manage the high cost of AI by right-sizing inference clusters and implementing caching layers to reduce token consumption.

The MLOps Tech Stack

You are the master of the "AI Infrastructure"

Orchestration & Workflow

Kubeflow, Airflow, or MLflow.

Model Serving

AWS SageMaker, Google Vertex AI, or Azure Machine Learning.

Vector Infrastructure

Pinecone, Weaviate, Milvus, or pgvector.

LLM Tooling

LangChain, LlamaIndex, and OpenAI/Anthropic Enterprise APIs.

Monitoring & Safety

Weights & Biases, Arize Phoenix, or WhyLabs for model health.

Core Languages

Python (Mastery), GoLang, and Bash.

Who You Are (Requirements)

The "Stability-First" Data Scientist

You care more about a model's P99 latency and Reliability than its sheer complexity.

The AI Safety Advocate

You understand the legal and ethical risks of AI in the enterprise and build systems that can be audited and "turned off" instantly if they deviate.

The Production Specialist

You have moved models out of Jupyter Notebooks and into high-traffic production environments where millions of users interact with them daily.

Experience

8+ years in DevOps or Data Science, with at least 2 years focused specifically on MLOps or AI infrastructure.

Why This Role is Critical at DuskByte

You are the reason our "Modernisation" isn't just about catching up to the present. It's about leaping into the future. You enable us to add StartDeck-level intelligence to legacy platforms safely. You turn AI from a "cool experiment" into a Mission-Critical Enterprise Feature.

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