Data Scientist - Machine Learning

As a Machine Learning Engineer, you will be responsible for leveraging your strong fundamentals and academic knowledge of Machine Learning algorithms and statistics to solve real-world problems. You will work with medium to large-scale datasets, including time-series, anomaly detection, text, and image data. Your tasks will involve conducting exploratory data analysis (EDA), curating high-quality datasets, and performing error analysis for ML and software algorithms. Your role will require you to design and implement ML solutions for various domains such as Computer Vision, NLP, LLMs, and VLMs. By following a methodical approach, you will formulate hypotheses, prototype models, and validate performance using measurable KPIs. You will also be expected to leverage advancements in GenAI and Agentic AI in your projects. Collaboration is a key aspect of this role as you will be working in international teams/projects, where maintaining strong communication and documentation standards is essential. Furthermore, you will need to apply MLOps best practices to ensure reproducibility, scalability, and deployment readiness of ML solutions. Using tools like Docker and other containerization/orchestration tools for ML workflows will be part of your daily tasks. Your required skills include expertise in Machine Learning frameworks such as Scikit-learn, TensorFlow, PyTorch, and a strong understanding of NLP & LLMs. Proficiency in vector search & similarity algorithms like FAISS, Milvus, Pinecone, and knowledge of cosine similarity, dot-product scoring, and clustering methods are also essential. Strong programming skills in Python with NumPy, Pandas, Scikit-learn, and ML/AI libraries are a must. Additionally, proficiency in version control with Git, collaborative coding practices, familiarity with Azure, Docker, and Kubernetes, and having an analytical mindset are important for success in this role. Your ability to produce high-quality documentation and work effectively in cross-functional teams will also be crucial. In summary, as a Machine Learning Engineer, you will play a vital role in designing and implementing ML solutions, collaborating with international teams, and aligning ML solutions with business objectives to achieve success in solving real-world problems.,