Ai Ml Engineer

AI/ML & Generative AI Developer
1-2 Years Experience | Tecorb Technologies
Noida | Full-Time | IT Services
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AI/ML & Generative AI Developer
1-2 Years
Noida
Full-Time
IT Services
About the Role
At Tecorb Technologies, we are building the future of intelligent systems by leveraging cutting-edge
AI/ML and Generative AI technologies.
We are looking for a driven and technically grounded developer with 1-2 years of hands-on experience
to join our AI/ML & Generative AI team. This role is suited for professionals who have moved beyond
entry-level exposure and are ready to take ownership of AI/ML pipelines, contribute to real-world
deployments, and grow into a senior AI engineer role. You will work on machine learning, deep
learning, large language models (LLMs), and generative AI systems including GPT models,
Transformers, diffusion models, and more.
If you connect dots, understand systems holistically, and are passionate about building intelligent
applications we want you.
Core AI/ML Knowledge Required
Machine Learning Fundamentals


Supervised, unsupervised, and semi-supervised learning paradigms
Classical ML algorithms: Linear/Logistic Regression, Decision Trees, Random Forests, SVMs,
Gradient Boosting (XGBoost, LightGBM)
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Model evaluation: cross-validation, bias-variance tradeoff, precision/recall, ROC-AUC
Feature engineering, data preprocessing pipelines, and handling imbalanced datasets
Hands-on experience with scikit-learn, NumPy, Pandas
Deep Learning & Neural Networks
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Solid understanding of feedforward networks, backpropagation, and optimization (Adam, SGD,
learning rate schedulers)
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Convolutional Neural Networks (CNNs) for image/vision tasks
Recurrent Neural Networks (RNNs), LSTMs, and GRUs for sequential data
Attention mechanisms and how they led to the Transformer architecture
Experience with PyTorch and/or TensorFlow/Keras for model training and fine-tuning
Transformers & Large Language Models
Transformers are the backbone of modern AI. Candidates must have strong knowledge of:

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Transformer Architecture Self-attention, multi-head attention, positional encoding,
encoder-decoder structure
BERT (Bidirectional Encoder Representations from Transformers) masked language
modeling, fine-tuning for classification, NER, QA
GPT Models (GPT-2, GPT-3, GPT-3.5, GPT-4) causal language modeling, prompt
engineering, in-context learning, and API integration
T5, FLAN-T5 encoder-decoder models for text-to-text tasks like summarization, translation,
and QA
LLaMA, Mistral, Falcon open-source LLM architectures, weight loading, and inference
optimization
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Hugging Face Transformers library model loading, tokenization, pipelines, and Trainer API
Tokenization strategies BPE, WordPiece, SentencePiece
Positional encodings absolute, relative (ALiBi, RoPE)
Generative AI Systems
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Generative Adversarial Networks (GANs) basics of generator-discriminator training
Variational Autoencoders (VAEs) latent space, reconstruction loss, KL divergence
Diffusion Models forward/reverse diffusion, DDPM, Stable Diffusion, ControlNet
Retrieval-Augmented Generation (RAG) vector retrieval, chunking strategies, reranking
Prompt engineering techniques zero-shot, few-shot, chain-of-thought, ReAct
Fine-tuning strategies full fine-tuning, LoRA, QLoRA, instruction tuning, RLHF basics
NLP Fundamentals
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Text preprocessing tokenization, lemmatization, stopword removal, vectorization (TF-IDF,
embeddings)
Core NLP tasks sentiment analysis, Named Entity Recognition (NER), text classification,
summarization, machine translation
Word embeddings Word2Vec, GloVe, FastText, and contextual embeddings from
Transformers
Semantic similarity, question answering, and dialogue systems
Key Responsibilities
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Design, build, fine-tune, and deploy ML models and generative AI pipelines with minimal
supervision
Integrate pre-trained models (GPT-4, LLaMA, Mistral, Stable Diffusion) into production
applications via APIs or custom backends
Implement end-to-end NLP systems chatbots, content generators, summarizers, and RAG
pipelines
Perform data preprocessing, feature engineering, and dataset curation for training and
evaluation
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Conduct model evaluation, benchmarking, error analysis, and iterative performance tuning
Explore and implement reinforcement learning techniques (RLHF, reward modeling) to improve
model interactions
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Build modular, scalable AI workflows using FastAPI, Docker, LangChain, and vector databases

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Stay current with AI research (arXiv, Hugging Face, OpenAI blogs) and prototype new ideas
rapidly
Write clear documentation for experiments, code, models, pipelines, and datasets
Required Skills & Qualifications
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Bachelors, Masters, or PhD in Computer Science, Data Science, AI/ML, or a related field
1-2 years of hands-on professional or project experience with ML/AI systems
Strong Python proficiency with ML libraries: scikit-learn, TensorFlow, PyTorch
Solid understanding of Transformer architecture and attention mechanisms
Practical experience working with GPT models via API (OpenAI, Azure OpenAI, Groq) or
open-source equivalents
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Working knowledge of Hugging Face ecosystem (Transformers, Datasets, PEFT)
Familiarity with LLM fine-tuning techniques: LoRA, QLoRA, or full fine-tuning
Understanding of vector databases and embedding workflows (FAISS, ChromaDB, Pinecone)
Knowledge of APIs, JSON, and RESTful application design
Proficiency with Git, Jupyter Notebooks, and Linux command-line tools
Nice to Have (Not Mandatory)
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Familiarity with MLOps tools: Weights & Biases, MLflow, DVC, or TensorBoard
Basic knowledge of reinforcement learning
What Youll Get
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Hands-on experience on real AI/ML projects and production-ready systems from day one
Mentorship and career development from senior AI/ML engineers and researchers
Access to state-of-the-art tools, compute infrastructure, and paid API credits
Opportunity to contribute to high-impact solutions in AI automation, GenAI workflows, and
enterprise applications
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A learning-driven, inclusive, and collaborative work environment
Fast growth track with exposure to client-facing work, research, and system design
We are looking for an Engineer who understands systems and connects the dots not just a developer.
Tecorb Technologies | Noida | tecorb.com