Data Scientist II - Machine Learning/Artificial Intelligence (3-6 yrs)

Ninjacart : Pioneer. Challenge Yourself. Create Better Lives.

Ninjacart is a pioneer in agritech. We believe in fostering a culture of innovation. We develop professionals who pioneer new ideas, simplify customer experiences, and impact the lives of millions. Our employees take complete ownership and truly belong.

Ninjacart is India's leading agri-platform, which leverages technology and data to organize the agri-commerce ecosystem. Over the last 9 years, our made-for-India technology and India-centric solutions have disrupted the way fruits and vegetables move from farms to consumers' plates. We empower farmers and other players in the ecosystem in ways never done before.

Ninjacart aims to be the digital network for global agri-commerce that solves structural problems such as information asymmetry, payment hassles, distribution inefficiency, and discovering new buyers and sellers with tech-first solutions.

Ninjacart has raised over $350mn from Walmart Group, Tiger Global, Accel US, Accel India, Syngenta, and others. We are one of the top 25 startups to work for, according to Linkedin.

We are a highly motivated, results driven community, who focus on proactive approaches to problem solving. We cherish entrepreneurial spirit and provide significant operating autonomy to senior leaders.

There are ample opportunities and challenges to be solved at scale and in real-time.

Location : Bangalore, KA, IN

About the Team :

The Ninjacart technical team consists of professionals from various backgrounds, including programming, design, architecture, databases, DevOps, security, analytics & machine learning. We work to create the first and biggest agricultural ecosystem in the world.

Responsibilities :

Machine Learning and AI :

- Develop and deploy machine learning models, including classical ML, deep learning, and

GenAI applications.

- Implement NLP solutions, computer vision models, and generative AI techniques.

- Collaborate on integrating AI models into web-based applications.

- Participate in fine-tuning large language models (LLMs) for various generative AI tasks,

Including :

- Adapting pre-trained LLMs to domain-specific agricultural tasks.

- Implementing different fine-tuning strategies (e.g., full fine-tuning, LoRA, prefix tuning).

- Optimizing LLMs for specific downstream tasks while maintaining general capabilities.

Data Analytics & Feature Engineering :

- Conduct exploratory data analysis to uncover patterns and trends in complex datasets.

- Lead feature engineering processes to improve model performance and interpretability.

- Utilize advanced analytical techniques such as clustering, segmentation, and time-series analysis.

MLOps and DevOps Integration :

- Implement MLOps practices to streamline the machine learning lifecycle.

- Use tools like DVC and MLflow for experiment tracking and model management.

- Collaborate with DevOps teams to integrate ML models into production environments.

Full Stack ML Engineering :

- Develop user-friendly and interactive machine learning applications using FastAPI and Streamlit.

- Integrate ML models into end-to-end solutions.

Model Evaluation and Optimization :

- Evaluate models for effectiveness and efficiency in real-world applications.

- Optimize models for performance, scalability, and resource utilization.

- Assess and compare the performance of fine-tuned LLMs using appropriate metrics and benchmarks.

- Collaboration and Continuous Learning

- Work with cross-functional teams to translate business requirements into ML solutions.

- Stay updated on the latest developments in ML, NLP, computer vision, and GenAI.

- Contribute to the company's innovation pipeline.

A Ninja is resilient, smart, and ambitious. Sounds like you? Heres what you will need to have to join the Ninja Clan

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

- Minimum of 3 years of proven experience in developing and deploying ML solutions, including NLP, computer vision, and classical ML models.

- Experience with GenAI techniques and applications, including LLM fine-tuning.

- Strong understanding of classical ML techniques, mathematical modeling, and statistical analysis.

- Proficiency in Python and relevant libraries (TensorFlow, PyTorch, Hugging Face transformers, OpenCV, FastAPI, Streamlit).

- Experience with MLOps practices and DevOps integration.

- Excellent problem-solving skills and ability to work independently or collaboratively.

Additional Information :

At Ninjacart, we are creating a workplace that enables everyone to find their true potential,

purpose, and passion irrespective of their background, gender, race, sexual orientation, religion

and ethnicity. We are committed to providing equal opportunity for all and believe that diversity

in the workplace creates a more vibrant, richer work environment that advances the goals of

our employees, communities and the business. Check out what Life at Ninjacart looks like!