Senior AI/ML Engineer

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., 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.

• 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.

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.