Senior AI/ML Engineer

We are looking for a Senior AI/MLEngineer who will be responsible for designing, developing, and deploying end-to-end AI and Machine Learning solutions that drive measurable business impact. This role is ideal for someone with strong expertise across the full data and AI lifecycle—from data discovery, analytics, and predictive modeling to Generative AI, Agentic AI, deployment, and continuous optimization in production environments.

The ideal candidate combines the mindset of a Data Scientist, ML and AI Engineer, with the ability to independently solve complex business problems using data, predictive models, and modern AI technologies.

Key Responsibilities

Data Science & Analytics

● Drive end-to-end data science initiatives, including data discovery, exploratory data analysis (EDA), statistical modeling, hypothesis testing, and business insights generation.

● Analyze large structured and unstructured datasets to identify trends, opportunities, anomalies, and actionable recommendations.

● Develop forecasting, optimization, recommendation, classification, clustering, and predictive analytics solutions.

● Translate business problems into measurable data science and AI outcomes.

Machine Learning Engineering

● Own ML projects end-to-end, including feature engineering, model development, evaluation, deployment, monitoring, and retraining.

● Design and implement scalable data ingestion and feature engineering pipelines.

● Develop and optimize supervised, unsupervised, reinforcement learning, and deep learning models.

● Build automated model retraining, monitoring, and performance optimization pipelines.

● Ensure model explainability, fairness, robustness, and responsible AI practices.

AI & Generative AI

● Design and develop AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.

● Build intelligent assistants, copilots, workflow automation agents, and AI-driven decision support systems.

● Integrate AI models with enterprise platforms, APIs, knowledge bases, and business workflows.

● Evaluate and optimize AI solutions using quantitative and qualitative performance metrics.

● Stay current with emerging AI technologies, frameworks, and best practices.

Collaboration & Leadership

● Partner with product managers, software engineers, data engineers, and business stakeholders to define AI and data strategies.

● Architect scalable AI/ML solutions aligned with business objectives and enterprise standards.

● Present technical findings, model outcomes, and business impact clearly to both technical and non-technical audiences.

● Mentor junior engineers and contribute to AI/ML best practices across the organization.

Required Qualifications

● Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Machine Learning, Statistics, Mathematics, or a related field.

● 5+ years of experience delivering Data Science, AI, and Machine Learning solutions in production environments.

● Strong expertise in Python and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, XGBoost, LangChain, and related ecosystems.

● Strong foundation in statistics, machine learning algorithms, predictive analytics, optimization techniques, and data modeling.

● Experience building end-to-end ETL/ELT pipelines, feature engineering workflows, and large-scale data processing solutions.

● Hands-on experience with ML lifecycle management, including model versioning, deployment, monitoring, and retraining.

● Experience working with cloud platforms such as GCP, AWS, or Azure for AI/ML workloads.

● Strong software engineering skills with knowledge of APIs, distributed systems, and scalable application architectures.

● Excellent analytical, problem-solving, and communication skills.

Preferred Skills

● Experience with Generative AI, LLMs, RAG architectures, vector databases, and Agentic AI frameworks.

● Experience with MLOps platforms and tools such as MLflow, Airflow, Kubeflow, Vertex AI, SageMaker, or Azure ML.

● Familiarity with data platforms such as BigQuery, Databricks, Spark, or similar technologies.

● Experience developing AI agents using frameworks such as LangGraph, CrewAI, AutoGen, or similar.

● Knowledge of optimization algorithms, operations research, and decision intelligence systems.

● Domain experience in logistics, supply chain, transportation, retail, e-commerce, or delivery platforms is highly desirable.

Location: Remote

Technology Stack: Python, SQL, BigQuery/Snowflake, TensorFlow, PyTorch, Scikit-learn, MLflow, Airflow, LangChain, LangGraph, Vector Databases, GCP/AWS/Azure, Docker, Kubernetes.