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 technology professionals interested in machine learning, artificial intelligence, software engineering, model development, backend systems, data processing, model deployment, APIs, MLOps, cloud technologies, generative AI, and production-grade AI applications.

The Machine Learning Software Engineer will work closely with software, IT, data, analytics, operations, production, supply chain, finance, sales, and other business teams to develop, test, deploy, integrate, maintain, and improve machine-learning models, intelligent applications, prediction services, data pipelines, APIs, automation solutions, analytics systems, and enterprise AI platforms.

The role may involve working with Python, NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, SQL, FastAPI, Flask, machine-learning algorithms, deep learning, generative AI, cloud platforms, Docker, Kubernetes, MLOps tools, data pipelines, model-serving technologies, and modern software-engineering practices depending on project and business requirements.

Qualifications

- B.E. / B.Tech / B.Sc. / BCA / MCA / M.Sc. / M.Tech in Computer Science, Information Technology, Software Engineering, Computer Applications, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Electronics, or a related discipline.
- Fresh graduates and experienced candidates are strongly encouraged to apply.
- Candidates with 0–5 years of experience in machine learning, artificial intelligence, ML engineering, software engineering, data science, Python development, model deployment, data engineering, or related technology roles can apply.
- Candidates currently working as Machine Learning Software Engineer, Machine Learning Engineer, ML Engineer, AI Engineer, AI/ML Engineer, Applied ML Engineer, Machine Learning Developer, Data Scientist, Python Developer, Software Engineer, AI Software Engineer, Associate Machine Learning Engineer, Graduate Software Engineer, or Junior ML Engineer are encouraged to apply.
- Candidates from IT services, SaaS, product companies, technology, consulting, e-commerce,



fintech, telecom, analytics, manufacturing, logistics, FMCG, or other industries are welcome.
- Basic to good knowledge of Python programming, object-oriented programming, data structures, algorithms, modules, packages, exception handling, debugging, and clean coding practices.
- Familiarity with NumPy, Pandas, scikit-learn, SciPy, or similar data-science and machine-learning libraries will be beneficial.
- Understanding of supervised learning, unsupervised learning, classification, regression, clustering, feature engineering, feature selection, model training, validation, and model evaluation.
- Basic knowledge of probability, statistics, linear algebra, data interpretation, and analytical concepts will be advantageous.
- Familiarity with TensorFlow, PyTorch, Keras, XGBoost, LightGBM, CatBoost, or similar machine-learning and deep-learning frameworks will be beneficial.
- Exposure to deep learning, neural networks, natural language processing, computer vision, recommendation systems, anomaly detection, forecasting, or time-series analysis will be advantageous.
- Familiarity with model evaluation metrics, cross-validation, hyperparameter tuning, model selection, overfitting, underfitting, regularization, and experimentation concepts will be beneficial.
- Exposure to generative AI, large language models, prompt engineering, embeddings, vector databases, retrieval-augmented generation, or similar technologies will be considered an advantage.
- Familiarity with Hugging Face, LangChain, LlamaIndex, OpenAI-compatible APIs, Transformers, or similar AI-development frameworks will be beneficial but is not mandatory.
- Basic to good understanding of SQL, MySQL, PostgreSQL, SQL Server, MongoDB, or similar databases.
- Familiarity with REST APIs, JSON, FastAPI, Flask, Django, or similar technologies for developing and serving machine-learning applications will be advantageous.
- Exposure to model deployment, inference APIs, batch prediction, real-time prediction, model serving, feature pipelines, and production ML systems will be beneficial.
- Familiarity with Git, GitHub, version control, branching, pull requests, code reviews, testing, and collaborative software-development workflows.
- Exposure to unit testing, API testing, PyTest, unittest, Postman, integration testing, or automated testing will be beneficial.
- Exposure to AWS, Microsoft Azure, Google Cloud, SageMaker, Azure Machine Learning, Vertex AI,



or similar cloud and AI platforms will be considered an advantage.
- Familiarity with Docker, Kubernetes, CI/CD, Jenkins, GitHub Actions, or similar deployment and DevOps technologies will be advantageous.
- Exposure to MLOps tools and practices such as MLflow, Kubeflow, Airflow, DVC, Weights & Biases, model versioning, experiment tracking, model registries, automated deployment, and model monitoring will be beneficial.
- Exposure to ETL/ELT, data pipelines, Spark, PySpark, Kafka, Databricks, dbt, Hadoop, or similar data-engineering technologies will be advantageous but is not mandatory.
- Familiarity with OpenCV, spaCy, NLTK, Transformers, or similar computer vision and NLP libraries will be considered an additional advantage.
- Basic understanding of model drift, data drift, explainability, responsible AI, bias, privacy, data security, model security, and ethical AI concepts will be beneficial.
- Exposure to Linux, command-line tools, virtual environments, dependency management, application deployment, logging, monitoring, and troubleshooting will be advantageous.
- Exposure to microservices, distributed systems, Redis, Kafka, RabbitMQ, caching, asynchronous processing, or scalable backend architectures will be considered an advantage.
- Familiarity with Java, C++, JavaScript, TypeScript, Go, or other programming languages will be beneficial but is not mandatory.
- Exposure to automation, business analytics, dashboards, ERP, CRM, manufacturing analytics, quality analytics, predictive maintenance, demand forecasting, or supply-chain analytics will be considered an additional advantage.
- Familiarity with Agile, Scrum, Jira, SDLC, technical documentation, requirements gathering, experimentation, sprint planning, or issue tracking will be advantageous but is not mandatory.
- Good analytical, mathematical, logical, debugging, troubleshooting, and problem-solving skills.
- Good communication, documentation, collaboration, and teamwork abilities.
- Ability to understand business and technical requirements and translate them into scalable, reliable, maintainable, secure, and production-ready machine-learning software solutions.
- Willingness to work in an on-site environment.
- Internship, academic project, machine-learning project, AI project, Python project, data-science project, Kaggle project, GitHub project, generative AI project, research project, hackathon, freelance assignment, startup project, or open-source contribution will be considered but is not mandatory.
- Candidates without previous full-time machine-learning experience can also apply.
- Solid willingness to learn new machine-learning algorithms, AI frameworks, software-engineering practices, cloud platforms, MLOps tools, and production AI technologies.

Job Location: Morena, Madhya Pradesh

Employment Type: Full-time, On-site

Experience: Freshers & 0–5 Years

📌 Machine Learning Software Engineer (Morena)
🏢 Saatvik Agro
📍 Morena