Role: Senior AI/ML Model Development Engineer

Location: Remote

Type; Fulltime

Position Overview

We are seeking an experienced Senior AI/ML Model Development Engineer to lead core machine learning model design, training, and algorithmic development to solve complex enterprise problems. Unlike traditional software application engineering or prompt wrappers, this role focuses on hands-on model engineering, architecture selection, fine-tuning, unsupervised learning, reinforcement learning, and custom algorithm design. You will own the full model lifecycle—from exploratory data analysis and custom feature engineering to deep model training, evaluation, optimization, and production deployment.

Key Responsibilities

Core Model Development & Algorithmic Engineering

● Algorithm Design & Custom Model Training: Design, build, train, and evaluate tailored machine learning models using supervised, unsupervised, and reinforcement learning techniques to address domain-specific challenges.

● Beyond Wrappers & Prompts: Go beyond high-level APIs to perform hands-on model architecture customization, loss function modification, pre-training, and fine-tuning (e.g.,

LoRA, QLoRA) on custom datasets.

● Unsupervised & Reinforcement Learning: Develop advanced unsupervised models for pattern discovery, clustering, and anomaly detection, as well as RL/RLHF frameworks to align model outputs with business objectives.

Model Training, Optimization & MLOps

● Model Training Pipelines: Construct distributed model training pipelines using frameworks such as PyTorch, TensorFlow, or JAX across high-performance compute clusters.

● Hyperparameter & Loss Optimization: Systematically perform hyperparameter tuning,

model quantization, pruning, and distillation to achieve target accuracy, low latency, and compute cost efficiency.

● Evaluation & Ground-Truth Testing: Establish rigor around model validation,

monitoring model drift, bias/hallucination analysis,



and building automated benchmark datasets.

Problem Solving & System Architecture

● Domain-Specific AI Solutions: Analyze multi-dimensional enterprise datasets (speech transcriptions, unstructured textual data, numerical logs) to formulate mathematical and statistical AI solutions.

● Productionization: Own the model lifecycle end-to-end, serving models via low-latency

APIs or embedded engines while monitoring live inference performance.

Qualifications & Key Requirements

Experience & Core Competencies

● Overall Experience: 8 years of software engineering or data science experience, with at least 4 years specifically dedicated to core machine learning model training,

deep learning, and algorithm development.

● Core ML & Statistical Mastery: Solid mathematical background (linear algebra,

calculus, probability, optimization theory) with proven experience implementing supervised, unsupervised, and reinforcement learning techniques.

● Model Building Stack: Expert proficiency in Python and deep learning frameworks

(PyTorch, TensorFlow, JAX, scikit-learn, XGBoost/LightGBM).

● Generative AI & LLM Engineering: Hands-on experience with pre-training or fine-

tuning open-weight foundation models (e.g., Llama, Mistral), context optimization, and model alignment techniques.

● Data & Feature Engineering: Proficiency with high-volume data tools (Pandas, NumPy,

SQL, PySpark) for feature engineering, text/speech dataset creation, and embedding generation.

Preferred Qualifications

● Solid knowledge of MLOps platforms (MLflow, Kubeflow, Weights & Biases) for model tracking and artifact management.

● Hands-on experience with speech processing (STT models/Whisper fine-tuning) or NLP sequence modeling.

● Experience with GPU optimization frameworks (CUDA, TensorRT, vLLM, DeepSpeed).

Pay: ₹1,500,000.00 - ₹1,800,000.00 per year

Experience

- Data science: 8 years (Required)
- artificial intelligence: 4 years (Required)
- Machine Learning: 4 years (Required)

Work Location: Remote

📌 Senior AI/ML Developer (India)
🏢 solve IT consultant
📍 India