Senior Machine Learning Engineer

Senior Machine Learning Engineer

Automations · Full-time · In-Person (Islamabad, PK) · Hours 6pm - 2am PKT

About Nysonian

Nysonian builds the next generation of global lifestyle brands, shaping how people travel, move, and live. We go beyond creating great products to build experiences that elevate everyday life and empower people around the world.

Our Fast-Growing Portfolio Includes:

• NOBL Travel - redefining modern travel with design, durability, and performance
• FLO Pilates - bringing Pilates into homes and wardrobes globally

With $350M+ in revenue, 400+ teammates across 8 countries, and 1M+ customers worldwide, we are shaping the brands that will define the next decade.

Core Values: Winners’ Mindset | Speed with Purpose | Thoughtful Innovation | Genuineness | No Ego, Full Ownership

The Opportunity

We are looking for an automation engineer who is genuinely comfortable building things, not just configuring them. You will work on our agentic AI systems (the ones that decide, take actions, and call tools on their own), write and improve the prompts and logic that guide them, and build the backend services that support them.

This is not a senior position. We are not expecting 6+ years of experience or a research background. What we do want is someone who has actually built something real in this space, a personal project that is publicly live, a hackathon build, or work from a previous job, and can talk about the decisions they made and why. If you have played with an LLM API, wired up a RAG pipeline, or built an agent that calls tools, and you enjoyed doing it enough to go deeper, this is likely a good fit.

What You'll Own

• Building and maintaining agentic workflows that read customer data, make decisions, and take real actions (refunds, order updates, escalations, and similar)
• Writing, testing, and refining prompts, including thinking through where a model is likely to hallucinate or get overconfident, and designing around it
• Building and scaling backend endpoints (using FastAPI, Flask, or Django) that serve these AI systems reliably in production, not just in a notebook
• Working with retrieval systems (RAG), embeddings, and vector search to ground responses in real data instead of the model's memory
• Reviewing and improving existing automations built in n8n, and helping decide when something should move from a no code workflow into real code
• Digging into a wrong or weird agent output, tracing it back through logs and executions, and fixing the actual root cause
• Staying current enough with the field that you naturally bring up a new model release, a new benchmark, or a new coding tool without being asked

Skills & Qualifications

• Solid hands on experience with agentic AI concepts: tool calling, multi step reasoning, memory, and orchestrating more than one agent to solve a problem
• Practical experience with at least one agent framework such as LangChain, LangGraph, CrewAI, AutoGen, or the OpenAI or Anthropic agent/assistant SDKs. We care more that you understand the concepts underneath than which specific framework you have used
• Real backend development experience in Python, with a framework such as FastAPI, Flask, or Django, including designing and deploying an API that other systems actually call
• A working understanding of NLP and how LLMs behave: context windows, tokens, embeddings, fine tuning versus retrieval, and why a model says confident things that are wrong
• Comfort with prompt engineering as an actual practice, not guesswork: iterating on a prompt, testing it against real cases, and knowing when the fix belongs in the prompt versus in the code around it
• A genuine foundation in data science and machine learning: you should be able to talk through a basic model training and evaluation workflow, know why accuracy is often the wrong metric, and be comfortable with Python's data stack (pandas, NumPy, scikit-learn)
• At least one real project, professional or personal, that touches this space. We would rather see one thing you built end to end than a long list of tools you have briefly touched
• Genuine curiosity about the field. You should already be someone who reads about new model releases, checks benchmark leaderboards, and tries out new AI coding tools on your own, not because a job requires it

Nice to have

• Experience with n8n, Zapier, or Make.com. Several of our internal systems are built this way, and being able to read, debug, or improve one of these workflows is genuinely useful, even though it is not the core of this role
• Experience with vector databases such as Pinecone, Weaviate, Chroma, or pgvector
• Familiarity with Postman or similar tools for API testing
• Exposure to MongoDB or PostgreSQL
• Experience using AI coding assistants day to day, such as Claude Code, GitHub Copilot, or Cursor

Tools and Technologies you will touch

Python, FastAPI, Flask, Django, LangChain, LangGraph, CrewAI, OpenAI and Anthropic APIs, n8n, vector databases (Pinecone, Chroma, or similar), pandas, NumPy, scikit-learn, PyTorch or TensorFlow at a basic level, Postman, Docker, PostgreSQL and MongoDB.

Why You'll Love Working at Nysonian

Culture

• We're founder-led and operate with speed, direct communication, and clear accountability
• We invest in tools and management practices that help colleagues do their best work
• Our products are used by customers globally
• AI is intentionally embedded in how we work, create, and scale
• Senior leaders are expected to create structure, make decisions, and stay close to execution

Growth & Development

• Competitive pay and meaningful opportunities for performance-based advancement
• Ownership of strategy, systems, execution, and team buildout within your function
• Opportunity to build and scale a meaningful part of the business across two consumer brands
• Scope and compensation growth tied to performance, role expansion, and measurable business impact

We are proud to be an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, sex, religion, gender, marital status, national origin, genetics, disability, age, veteran status or other characteristics.