We’re looking for a highly motivated AI/ML Engineer to join our dynamic team and contribute to the development of cutting-edge intelligent search systems. This role will center around vector-based retrieval systems, embedding models, and semantic search technologies that push the boundaries of how machines understand and process language.
This is a high-impact role where you'll have the opportunity to drive innovation, collaborate with multi-disciplinary teams, and work with some of the most exciting tools and frameworks in the AI/ML ecosystem.
What You’ll Be Doing
- Vector Search System Development. Design, build, and optimize vector-based search architectures using tools such as FAISS, Milvus, Weaviate, or Pinecone. Ensure low-latency and high-accuracy search capabilities in large-scale datasets.
- Semantic Search Implementation. Apply semantic similarity models and embedding techniques to enable context-aware and meaningful search experiences. Work with transformer-based architectures like BERT, RoBERTa, and GPT variants to power intelligent information retrieval.
- R&D and Prototyping. Stay abreast of emerging trends in natural language processing (NLP), approximate nearest neighbor (ANN) search, and vector databases. Run experiments, develop POCs, and evaluate new models/tools to continuously improve system efficiency and accuracy.
- Collaboration & Communication. Work closely with data scientists, software engineers, and product stakeholders to integrate ML models into production systems. Document findings, methodologies, and implementation processes clearly and effectively.
Core Skills & Qualifications
- Machine Learning Expertise. Solid experience in training, fine-tuning, and deploying machine learning and deep learning models.
- Natural Language Processing (NLP). Strong foundation in language embeddings, transformer architectures, and semantic modeling. Hands-on with Hugging Face Transformers, SpaCy, or similar libraries.
- Vector Search Technologies. Proficiency with tools like FAISS, Milvus, Weaviate, or Pinecone to implement scalable and efficient vector similarity search.
- Similarity & Ranking Algorithms. Deep understanding of cosine similarity, dot-product scoring, lexical vs semantic search, vector quantization, and clustering techniques.
- Programming Proficiency. Strong skills in Python and its ML ecosystem (NumPy, Pandas, Scikit-learn). Experience in writing production-ready, modular, and testable code.
- Cloud and DevOps Tools. Familiarity with Azure cloud services, Docker, Kubernetes, and deployment pipelines for ML workloads.
- Communication & Teamwork. Ability to communicate complex ideas effectively across technical and non-technical teams. Capable of writing clear technical documentation and presenting solutions in a cross-functional setting.
Preferred (Nice-to-Have) Skills
- Experience with hybrid search techniques that blend traditional (Elasticsearch, Solr) and vector-based retrieval.
- Knowledge of vector quantization and storage optimization techniques for high-volume datasets.
- Exposure to recommendation systems, knowledge graphs, or graph-based retrieval.
- Hands-on experience working in Proof of Concept (PoC) teams to validate innovative ML approaches.
Education & Experience
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a closely related field.
- 5+ years of professional experience in AI/ML, with a strong focus on NLP, vector search, and deep learning technologies.
Why Join Us?
- Work remotely with top AI talent and forward-thinking teams from across the globe.
- Contribute to high-impact projects in the ever-evolving space of semantic search and intelligent systems.
- Be part of a collaborative, innovative, and transparent culture that values curiosity and continuous learning.
- Get access to the latest tools and platforms in AI/ML development.
- Competitive compensation in the range of ?45–55 LPA for top-tier talent.
If you're ready to build intelligent systems that truly understand human language and have the skills and hunger to match, apply now and start immediately.