Machine Learning Engineer

SalesCodeAI INTRODUCTION :

About Founded by Ex Coke business leaders, SalesCodeAI is the the NextGen AI Platform for "Future Ready Sales Team and Trade" with AI and eB2B for CPG Industry.

SalesCode is possibly the only Enterprise SaaS platform that guarantees a minimum Sales Uplift of 3%. We promise to pay a penalty with a 110% refund if we do not deliver !!

With 3M+ Users across 18 countries, we are already working at scale with top global companies like Coca Cola, PepsiCo, Colgate, Johnson & Johnson, P&G, Mondelez, MARS, Reckitt, Perfetti, BATA, and others.

An AI-powered SaaS Platform for Sales and RTM, SalesCode augments the competency of each Sales Rep and connects the B2B customers for real-time transactions and engagement, with guaranteed Sales Up-lift.

Job Summary :

We are looking for a talented and motivated Machine Learning Developer who brings together strong foundational skills in ML and Deep Learning, hands-on experience with Java or Python, and a solid understanding of big data pipelines such as Apache Spark. This role requires familiarity with batch processing, event streaming, and the application of Generative AI (GenAI) models in real-world scenarios.

Key Responsibilities :

- Design, develop, and deploy machine learning and deep learning models using PyTorch, TensorFlow, or similar frameworks.

- Develop and integrate GenAI - based solutions such as large language models (LLMs) and text generation into production systems.

- Work with big data pipelines and event-driven architectures using Apache Spark and Kafka.

- Collaborate with cross-functional teams to integrate ML/DL models into business applications.

- Handle preprocessing, feature engineering, and performance optimization for large-scale datasets.

- Conduct experiments, evaluate models, and iterate based on feedback and results.

- Ensure robustness, scalability, and maintainability of ML solutions in production.

- Monitor model behavior and data quality post-deployment.

Required Skills & Qualifications :

- Solid understanding of machine learning concepts and hands-on experience with ML algorithms.

- Proficiency in Java and/or Python for model development and data manipulation.

- Experience with deep learning frameworks such as TensorFlow or PyTorch.

- Hands-on experience with Generative AI techniques and foundational models.

- Strong grasp of Apache Spark for batch processing and Kafka for event streaming.

- Ability to work with large-scale, distributed data environments.

- Knowledge of data formats like Parquet, Avro, and optimization strategies for data storage and retrieval.

- Familiarity with model deployment workflows and versioning.

Nice to Have :

- Experience with ML lifecycle tools such as MLflow, Weights & Biases, or Kubeflow.

- Understanding of data lake technologies like Apache Iceberg or Delta Lake.

- Knowledge of containerization and orchestration using Docker and Kubernetes.

- Exposure to cloud environments (AWS/GCP/Azure) for model training and deployment.

- Familiarity with LLM fine-tuning, embeddings, and prompt engineering.

Education :

- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related technical field.