AI/ML Trainee Engineer (LLM & Applied ML)

ARCK AI Softtech Technology Pvt. Ltd.

Location:

[City / Remote / Hybrid] · Type:

Full-time trainee programme, [6/12] months with conversion on performance · Experience:

0–1 years ·

About ARCK AI

ARCK AI is a technology company solving complex problems for organisations of every size. We specialise in AI automation, cybersecurity, cloud migration, application development, and network and security solutions — combining deep technical expertise with a bold approach to problem-solving.

We deliver for clients across the US, UK, and the Middle East, and we value diverse perspectives and talents in the people who build with us.

About the role

We build AI systems that run in production — LLM applications, RAG pipelines, AI agents, and applied machine learning.

This is not a research internship and not a training-room programme. You join an AI delivery pod from month one, with a senior engineer mentoring you, and you ship to real users. The gap between a working demo and a production system is most of the job, and closing it is what you will learn here.

What you'll do

- Build and ship features in LLM-powered applications — retrieval, prompting, tool calling, agent workflows
- Work on RAG pipelines end to end: chunking strategy, embeddings, vector search, reranking, and grounding
- Write evaluation harnesses and test sets, and use them to prove a change actually improved the output
- Handle the data side — cleaning, labelling, and building the ingestion pipelines models depend on
- Train, fine-tune, and benchmark models for narrower tasks: classification, extraction, prediction
- Deploy and monitor what you build — containerise it, put it behind an API, watch latency, cost, and quality in production
- Sit on client calls and translate a vague business ask into a scoped, testable AI problem

What we're looking for
- A degree in Computer Science, Engineering, IT, Data Science, Mathematics, Statistics, or a related field — completed, or in your final year
- Strong Python,



with a working knowledge of pandas and NumPy, and the habit of writing code others can read and maintain
- Solid CS foundations: data structures, algorithms, OOP, and sound software engineering practice
- Working understanding of ML fundamentals — train/test splits, overfitting, evaluation metrics, and why accuracy is usually the wrong one
- Practical exposure to LLM APIs (OpenAI, Anthropic, Gemini, or open-weight models), through a project, an internship, or your own experiments
- Git, and comfort on the Linux command line
- Some back-end exposure — building an API, querying a database, or working with a server-side framework
- Clear written and spoken English; you will be on calls with international clients
- Evidence that you build things: a GitHub profile, a deployed project, Kaggle work, a paper, or open-source contributions

Nice to have Not required — but these will make your application stand out.
- PyTorch or TensorFlow beyond tutorial level
- A vector database (pgvector, Pinecone, Qdrant, Weaviate, Chroma) used in something you actually shipped
- LangChain, LlamaIndex, or any agent framework
- SQL and exposure to data pipelines (Airflow, dbt)
- Docker, or any cloud platform — AWS, Azure, or GCP
- An understanding of where LLMs fail: hallucination, prompt injection, evaluation drift

What you get
- A named mentor and a defined 90-day learning plan
- Real client AI projects from your first month, not sandbox exercises
- Access to frontier model APIs and GPU compute for project work
- Support for certification and course costs after you clear probation
- A transparent conversion path to a full-time AI/ML Engineer role

How to apply Send your CV and a link to your GitHub, portfolio, or Kaggle profile to h [email protected] with the subject line "AI/ML Trainee"

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Include three or four lines on one AI or ML project you have built: what it did, what you got wrong the first time, and how you knew it improved. We read that part first — it tells us more than a CGPA does.

ARCK AI is an equal opportunity employer. We hire on capability.

#Hiring #AIJobs #MachineLearning #LLM #GenAI #FresherJobs #ArckAI

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