Junior AI Engineer

About the role

We are looking for a motivated Junior AI Engineer to join our Engineering – Artificial Intelligence & Machine Learning team in the United States. In this role, you will work closely with senior engineers and data scientists to design, build, and deploy AI and machine learning solutions that solve real business problems.

This is an excellent opportunity for a mid-level professional who is passionate about artificial intelligence and eager to take on greater ownership in a collaborative, fast-paced environment. You will gain hands-on exposure to modern AI/ML stacks, real-world production systems, and cross-functional collaboration across product, data, and QA teams.

Key Responsibilities:

Assist in designing, developing, and training machine learning and AI models under the guidance of senior team members.

Collect, clean, and preprocess structured and unstructured data for model development.

Support the deployment, monitoring, and maintenance of AI models in production environments.

Write clean, efficient, and well-documented code in Python and related frameworks.

Collaborate with cross-functional teams including data engineers, product managers, and QA to deliver AI-driven features.

Conduct experiments, evaluate model performance, and iterate based on results.

Stay up to date with emerging AI/ML tools, research, and best practices.

Document processes, findings, and technical decisions clearly for the team.

Participate in code reviews and contribute to a culture of continuous improvement.

Tech Stack:

Languages: Python (primary), SQL

ML/DL Frameworks: Scikit-learn, TensorFlow, PyTorch

LLM/GenAI Tools: OpenAI API, Hugging Face, LangChain

Data Tools: NumPy, Pandas, Jupyter Notebook

Cloud Platforms: AWS, Azure, or Google Cloud Platform (GCP)

MLOps & Deployment: Docker, Git/GitHub, CI/CD pipelines, Kubernetes (basic exposure)

Databases: PostgreSQL/MySQL, MongoDB or other NoSQL databases

Visualization & Reporting: Matplotlib, Seaborn, Power BI / Tableau

Required Qualifications:

Bachelor's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field.

3–5 years of hands-on experience in AI, machine learning, or software development.

Solid understanding of Python programming and common ML libraries such as NumPy, Pandas, and Scikit-learn.

Basic knowledge of machine learning concepts including supervised and unsupervised learning, model evaluation, and data preprocessing.

Familiarity with at least one deep learning framework such as TensorFlow or PyTorch.

Understanding of fundamental data structures, algorithms, and software engineering principles.

Working knowledge of version control systems such as Git.

Strong analytical and problem-solving skills with attention to detail.

Good communication skills and the ability to work effectively in a team environment.

Legally authorized to work in the United States.

Nice to Have:

Exposure to Large Language Models (LLMs), NLP, or Generative AI projects (academic or personal).

Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

Knowledge of MLOps tools and practices including Docker, Kubernetes, or CI/CD pipelines.

Familiarity with SQL and working with relational or NoSQL databases.

Experience with data visualization tools such as Matplotlib, Seaborn, or Power BI.

Contributions to open-source AI/ML projects, Kaggle competitions, or a personal GitHub portfolio.

Understanding of REST APIs and how to integrate ML models into applications.

Relevant certifications in AI, Machine Learning, or Cloud Computing.