Highlights
Join our vibrant startup culture; apply modern ML/DL techniques; collaborate on diverse projects.
Description
Job Summary
pWe are seeking a versatile and proactive Data Scientist to join our dynamic team. This role demands critical thinking and effective communication skills to apply data science and problem-solving techniques to complex real-world problems. Ideal candidates should have strong Python programming skills and expertise in machine learning algorithms.
Responsibilities
- Deliver end-to-end data science projects by applying ML/DL fundamentals.
- Develop high-quality software solutions with Python and other languages.
- Build and deploy production-ready LLM applications using modern frameworks.
- Implement RAG architectures for complex automation tasks.
- Evaluate and benchmark LLM outputs using metrics and testing frameworks.
Required Skills
- Python programming
- Machine Learning algorithms
- LLM orchestration frameworks
- Data pipeline orchestration tools
- SQL optimization techniques
Required Skills Explained
- Strong Python programming skills with hands-on project experience.
- Expertise in Machine Learning and Deep Learning algorithms including Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, and Ensemble methods.
- Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas.
- Familiarity with modern ML techniques such as Transfer Learning, Few-shot Learning, and Self-supervised Learning.
- Hands-on experience with LLM providers like OpenAI, Anthropic Claude, Google Gemini, or open-source models.
- Proficiency with GenAI orchestration frameworks including LangChain, LangGraph, LlamaIndex, or DSPy.
- Experience building RAG applications using vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
- Strong prompt engineering skills and understanding of prompt optimization techniques.
- Knowledge of fine-tuning techniques like LoRA, QLoRA, and when to apply them.
- Understanding of LLM evaluation metrics and benchmarking methodologies.
- Familiarity with agentic AI architectures and multi-agent systems.
- Experience with MLOps practices and tools such as MLflow, Kubeflow, or Weights & Biases.
- Proficiency with containerization using Docker and orchestration with Kubernetes.
- Experience with cloud platforms like AWS, Azure, or GCP for ML model deployment and monitoring.
- Understanding of CI/CD pipelines for ML applications.
- Knowledge of model serving frameworks and API development such as FastAPI, Flask, or Django.
- Solid understanding of SQL including advanced concepts like windowing functions and query optimization.
- Experience with data pipeline orchestration tools like Airflow or Prefect.
- Familiarity with both SQL and NoSQL databases.
Who is this for
pThis role is perfect for Data Scientists with a passion for cutting-edge AI/ML technologies. Ideal candidates should have strong technical skills and the ability to work in a fast-paced, collaborative environment.
Why This Job is a Good Opportunity
ulliTo work in a vibrant startup culture that values intellectual curiosity, continuous learning, positive work environment, and collaborative problem-solving.liTo join a dynamic team of dedicated professionals focused on solving complex data challenges for companies worldwide using cutting-edge Data Science and Data Engineering solutions.liTo be part of rapidly growing projects where you can apply modern AI/ML technologies and make significant contributions to the industry.liTo collaborate with developers and clients, translating business requirements into innovative data science solutions.liTo gain exposure to a wide range of real-world problems and develop your skills in diverse areas like NLP, Computer Vision, Time Series Analysis, and more.
Interview Preparation Tips
- Review core programming concepts in Python, especially focusing on ML libraries like TensorFlow or PyTorch.
- Pick a few Machine Learning algorithms (e.g., Random Forests, Neural Networks) to understand deeply and prepare examples of their applications.
- Practice building LLM applications using frameworks like LangChain and familiarize yourself with RAG architectures.
- Work on prompt engineering exercises and fine-tuning techniques for various use cases.
- Brush up on MLOps practices, especially containerization and CI/CD pipelines for ML models.
- Prepare examples of data pipeline orchestration using tools like Airflow or Prefect.
- Pretend to solve a real-world problem related to Data Science and explain your thought process and solution strategy.
Career Growth in This Role
pThe role offers excellent opportunities for career growth as you will be working on diverse, cutting-edge AI/ML projects. With continuous learning and the opportunity to stay updated with the latest technologies, you can advance from a Data Scientist I to a II or even higher within a short period. The company’s rapid growth also provides numerous opportunities to take on more responsibilities and lead impactful projects.pAs you gain experience, you may have the chance to mentor junior team members, contribute to open-source AI/ML projects, publish research papers, and present at conferences. This role is perfect for those looking to advance their careers in a fast-paced, innovative environment where your technical expertise will be highly valued.
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Skills
Frequently Asked Questions
What kind of projects will I work on?You'll work on end-to-end data science projects involving machine learning, deep learning, and building production-ready LLM applications.
What are the core responsibilities?Deliver complex ML/DL projects, develop software solutions, build LLM applications, and optimize database performance.
Is continuous learning encouraged?Absolutely! We value continuous learning and provide opportunities for growth and development in AI/ML technologies.
