Junior Machine Learning EngineerJob Title Junior Machine Learning Engineer
Job Summary We are looking for a passionate Junior Machine Learning Engineer to join our AI and Data Science team. This role is ideal for recent graduates or early-career professionals who are eager to build, train, and deploy machine learning models while working on real-world AI applications. You will collaborate with experienced engineers and data scientists to develop scalable machine learning solutions and contribute to the end-to-end ML lifecycle.
Key Responsibilities - Assist in designing, developing, and deploying machine learning models for business applications.
- Collect, clean, preprocess, and analyze structured and unstructured data.
- Build and evaluate machine learning models using supervised and unsupervised learning techniques.
- Perform feature engineering, model training, hyperparameter tuning, and performance evaluation.
- Develop data pipelines and automate ML workflows.
- Support model deployment, monitoring, and performance optimization in production environments.
- Collaborate with data scientists, software engineers, and product teams to deliver AI-driven solutions.
- Document experiments, model performance, and technical implementations.
- Stay up to date with the latest machine learning tools, frameworks, and best practices.
Required Qualifications - Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Information Technology, Statistics, Mathematics, or a related field.
- 0-2 years of experience in machine learning, data science, or software development (internships and academic projects are welcome).
- Strong understanding of machine learning fundamentals, statistics, and data analysis.
- Proficiency in Python programming.
- Experience with machine learning libraries such as Scikit-learn, PyTorch, or TensorFlow.
- Knowledge of data structures, algorithms, and object-oriented programming.
- Familiarity with SQL and relational databases.
- Experience using Git for version control.
Preferred Qualifications - Exposure to Natural Language Processing (NLP), Computer Vision, or Generative AI.
- Familiarity with Large Language Models (LLMs) and AI application development.
- Knowledge of data visualization tools such as Matplotlib, Seaborn, or Plotly.
- Basic understanding of cloud platforms (AWS, Azure, or Google Cloud).
- Experience with Docker and Linux.
- Academic, internship, or personal machine learning projects available on GitHub.
Technical Skills - Python
- SQL
- Scikit-learn
- PyTorch or TensorFlow
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Git
- Docker (basic)
- Linux (basic)
- Jupyter Notebook
Soft Skills - Strong analytical and problem-solving abilities.
- Eagerness to learn and grow in machine learning and AI.
- Good communication and teamwork skills.
- Attention to detail and commitment to writing high-quality code.
- Ability to work in a collaborative and fast-paced environment.
Nice to Have - Internship experience in machine learning or data science.
- Knowledge of MLOps concepts and model deployment.
- Familiarity with REST APIs and microservices.
- Exposure to data engineering tools and ETL pipelines.
- Participation in hackathons, coding competitions, or open-source AI projects.
Benefits - Competitive salary and performance-based incentives.
- Mentorship from experienced machine learning professionals.
- Learning and certification opportunities.
- Flexible work arrangements.
- Access to modern AI and ML tools and technologies.
- Opportunity to work on real-world machine learning projects with cross-functional teams.
