AI / Machine Learning Engineer

AI / Machine Learning Engineer Overview

We are seeking a highly skilled AI / Machine Learning Engineer to design, build, and deploy intelligent systems that enhance decision-making, automation, and product capabilities. The ideal candidate will have strong experience in machine learning, deep learning, data engineering practices, and cloud-based model deployment.

Key Responsibilities

Develop, train, and optimize ML and deep learning models using Python and modern frameworks (TensorFlow, PyTorch, Scikit-learn).

Build scalable end-to-end pipelines for data ingestion, preprocessing, feature engineering, model training, validation, and deployment.

Research, prototype, and implement new algorithms for computer vision, NLP, predictive analytics, and generative AI.

Collaborate with data engineers, product teams, and software developers to integrate ML solutions into production systems.

Deploy and manage models using cloud platforms (AWS, GCP, Azure) and MLOps tools.

Monitor model performance, drift, and quality; maintain continuous improvements through retraining and tuning.

Work with large-scale datasets to extract insights and improve predictive accuracy.

Document models, experiments, and architecture clearly for cross-functional teams.

Ensure ML systems follow best practices for security, compliance, and ethical AI standards.

Required Skills & Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or related field.

Strong hands-on experience with Python , TensorFlow , PyTorch , Keras , Scikit-learn , etc.

Solid understanding of machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers).

Experience with cloud platforms : AWS (SageMaker), GCP (Vertex AI), or Azure ML.

Strong knowledge of SQL , data structures, algorithms, and statistics.

Experience building APIs and deploying ML models using Docker, Kubernetes, or serverless technologies.

Familiarity with MLOps pipelines, MLflow, Kubeflow, or similar tools.

Ability to work with large datasets and use tools like Spark, Databricks, or Snowflake.

Excellent problem-solving and analytical skills.

Preferred Qualifications

Experience with Generative AI , LLM fine-tuning, RAG, vector databases (Pinecone, FAISS).

Experience in NLP tasks like summarization, sentiment analysis, entity extraction, or embeddings.

Experience with real-time model inference or streaming data (Kafka, Flink).

Knowledge of reinforcement learning or optimization techniques.

Publications, Kaggle experience, open-source contributions.

Soft Skills

Strong communication and documentation skills.

Ability to collaborate with cross-functional teams.

Self-driven, curious, and highly innovative mindset.

Ability to work in an agile environment.

Benefits (Optionally Add)

Competitive salary and performance bonuses.

Healthcare, dental, and retirement plans.

Remote / hybrid work options.

Professional development, certifications, and conference sponsorship.