AI Engineer

Hiring W2 Candidates Only

Visa : Open To Any Visa Type With Valid Work Authorization In the USA

Job Summary

We are seeking a talented AI Engineer to design, develop, and deploy artificial intelligence and machine learning solutions that solve complex business problems. The ideal candidate will have a solid foundation in data science, software engineering, and cloud-based AI tools, with the ability to operationalize AI models at scale.

Key Responsibilities

Design, develop, and implement machine learning (ML) and deep learning (DL) models to address business and operational challenges.

Collaborate with data scientists , data engineers , and software developers to build end-to-end AI pipelines.

Preprocess, clean, and analyze large datasets to ensure data quality and usability.

Deploy and monitor ML models in production environments (on-premise or cloud).

Optimize model performance through hyperparameter tuning , feature engineering , and model retraining .

Build and integrate AI APIs , including NLP, computer vision, and predictive analytics components.

Develop automation scripts and reusable frameworks for model training and inference.

Work with cloud AI services (AWS SageMaker, Azure AI, Google Vertex AI) to scale solutions.

Document workflows, model architectures, and deployment procedures.

Stay current on emerging AI trends, frameworks, and best practices.

Required Skills and Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field .

3+ years of experience in AI / ML engineering or applied machine learning .

Strong proficiency in Python and libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, pandas .

Experience with ML lifecycle management — from data preprocessing to deployment and monitoring.

Solid understanding of machine learning algorithms , neural networks , and statistical modeling .

Hands-on experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI).

Experience building and consuming RESTful APIs and working with microservices architectures .

Familiarity with data pipelines , ETL processes , and data versioning tools (e.g., DVC, MLflow).

Strong understanding of MLOps , CI / CD , and containerization (Docker, Kubernetes).

Excellent communication skills and ability to work collaboratively across multidisciplinary teams.

Preferred / Nice-to-Have Skills

Experience with Natural Language Processing (NLP) using Hugging Face, spaCy, or transformers.

Exposure to computer vision (OpenCV, YOLO, Detectron2).

Knowledge of reinforcement learning or generative AI (LLMs, diffusion models) .

Experience with big data tools (Spark, Hadoop) and data lakes .

Familiarity with DevOps and model observability tools (Prometheus, Grafana, EvidentlyAI).

Contributions to open-source AI projects or publications in AI / ML.

Example Technology Stack

Languages : Python, SQL, Bash

Libraries / Frameworks : TensorFlow, PyTorch, scikit-learn, Keras, Transformers

Tools : MLflow, Airflow, Docker, Kubernetes, Git

Cloud : AWS SageMaker, Azure ML, Google Vertex AI

Databases : PostgreSQL, MongoDB, BigQuery, Snowflake

Soft Skills

Strong analytical and problem-solving ability.

Curiosity for emerging AI trends and practical applications.

Excellent teamwork and communication in cross-functional environments.

Ability to explain technical AI concepts to non-technical stakeholders.