Machine Learning Software Engineer

Company Description
Saatvik Agro is the agro-ingredient unit of the Saatvik Group, specializing in high-quality maize-based ingredients used in food, nutrition, animal feed, and industrial applications. The organization focuses on purity and scientific rigor, converting responsibly sourced maize into functional and reliable ingredient solutions. Its products are designed to meet the evolving needs of modern manufacturers who demand consistency, performance, and safety. Guided by the belief that better ingredients create better outcomes, Saatvik Agro aims to support customers in delivering superior products to their markets.
Role Description
We are looking for a Machine Learning Software Engineer for a full-time, on-site opportunity based in Morena, Madhya Pradesh, India.
The role is suitable for fresh graduates and early-career technology professionals interested in working across Machine Learning, Artificial Intelligence, Python, Software Engineering, Data Science, Model Deployment, APIs, MLOps, Cloud, and Data Engineering.
The Machine Learning Software Engineer will work closely with software, data, IT, analytics, operations, production, finance, supply chain, sales, and other business teams to develop, integrate, deploy, and improve machine-learning solutions and intelligent software applications.
Qualifications
B.E. / B.Tech / B.Sc. / BCA / MCA / M.Sc. / M.Tech in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Mathematics, Statistics, Computer Applications, or a related discipline.
Freshers and experienced candidates are strongly encouraged to apply.
Candidates with 0–5 years of experience in machine learning, AI, software engineering, data science, Python development, MLOps, data engineering, or related technology roles can apply.
Candidates currently working as Machine Learning Engineer, Machine Learning Software Engineer, AI Engineer, Software Engineer, Data Scientist, Python Developer, Data Engineer, MLOps Engineer, Applied AI Engineer, or Associate Software Engineer are encouraged to apply.
Candidates from IT services, SaaS, product companies, technology, consulting, fintech, e-commerce, telecom, manufacturing, logistics, analytics, or other industries are welcome.
Basic to good knowledge of Python programming.
Understanding of machine learning, statistics, data structures, algorithms, and software-development fundamentals.
Familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, or similar ML frameworks will be beneficial.
Basic understanding of data preprocessing, feature engineering, model training, validation, evaluation metrics, and hyperparameter tuning.
Familiarity with SQL, MySQL, PostgreSQL, MongoDB, or similar databases will be an advantage.
Exposure to REST APIs, Flask, FastAPI, Django, or backend-development frameworks will be beneficial.
Familiarity with Git, GitHub, version control, testing, debugging, and collaborative software-development workflows.
Exposure to AWS, Microsoft Azure, Google Cloud, Databricks, SageMaker, Vertex AI, Azure Machine Learning, or similar platforms will be an advantage but is not mandatory.
Exposure to Docker, Kubernetes, MLflow, Airflow, Kubeflow, CI/CD, or MLOps tools will be beneficial but is not mandatory.
Knowledge of data visualization, analytics, and exploratory data analysis will be beneficial.
Exposure to NLP, computer vision, deep learning, generative AI, LLMs, forecasting, optimization, or recommendation systems will be an advantage but is not mandatory.
Basic understanding of model deployment, monitoring, retraining, and production ML systems will be beneficial.
Good analytical, mathematical, logical, debugging, and problem-solving skills.
Good communication, documentation, and teamwork abilities.
Ability to work effectively with software, data, analytics, and business teams.
Willingness to work in an on-site environment.
Internship, machine-learning project, Kaggle project, GitHub project, hackathon, AI project, research project, freelance work, or academic project will be considered but is not mandatory.
Strong willingness to learn new machine-learning, AI, software, data, cloud, and MLOps technologies.

Work arrangement
No