Cognologix
Sr. Data Science Engineer
Job Description
You will work on:
We are looking for self driven Data Professional to be a key member of our Data Practice. We help many of our clients make sense of their large investments in data – be it building analytics solutions or machine learning applications or Generative AI based solution. You will work on cutting edge cloud-native technologies to build meaningful insights.
Job Location: Bengaluru/Hyderabad/Kolkata/Mumbai What you will do (Responsibilities):
We are looking for self driven Data Professional to be a key member of our Data Practice. We help many of our clients make sense of their large investments in data – be it building analytics solutions or machine learning applications or Generative AI based solution. You will work on cutting edge cloud-native technologies to build meaningful insights.
Job Location: Bengaluru/Hyderabad/Kolkata/Mumbai What you will do (Responsibilities):
- Perform high-level work both independently and collaboratively as a project member or leader on multiple projects.
- Collaborate with Product Management team, elicit AI/ML use case specific requirements, explore and evaluate approaches
- Own the end-end process, from recognizing the problem to implementing the solution
- Develop NLP, Machine learning, Deep Learning, Gen AI based applications & demos according to pre-sales requirements and needs.
- Select appropriate datasets and data representation methods.
- Explore new tools, technologies, frameworks in ML, DL, Gen AI technologies and experiments.
- Keep abreast of developments in the field.
- Mentor, guide junior team members
What you bring (Skills):
- Sound knowledge in Linear Algebra, Statistics, Probability & various ML Algorithms (like KNN, SVM, Regression, Decision Trees, K-Means, Naive Bayes, GBM and Decision Forests etc)
- Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, scikit-learn, NLTK etc.
- Familiarity with deep learning, machine learning and NLP/NLG frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.)
- Experience with Natural Language Processing, Natural Language Understanding and Deep Learning algorithms
- Familiarity with deep learning architectures used for text analysis, computer vision and signal processing.
- Experience in Generative AI /LLM’s frameworks & technologies
- Experience in Prompt Engineering & Langchain / LlamaIndex, Vector search, RAG frameworks, Agents
- Experience in Cloud-based services such as AWS (Primary), Azure or GCP
- Understanding of how to operationalize these models to run in an automated context
- Strong development experience using Python or R and SQL
- Excellent analytical, problem solving and communication skills
Great if you know (Skills):
- Experience with Scrum and/or other Agile development processes
- Exposure to MlOps – model and experiment versioning, hyper parameter tuning, model deployment and monitoring aspects
- Sound understanding of data visualization aspects
- Ability to lead R&D and POC efforts . Experience in pre-sales is desirable.
- Team player with self-drive to work independently
- A track record of delivery within a number of large-scale projects, demonstrating ownership of architecture solutions and managing change
- Experience in manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
Advantage Cognologix:
- A higher degree of autonomy, startup culture & small teams
- Opportunities to become an expert in emerging technologies
- Remote working options for the right maturity level
- Competitive salary & family benefits
- Performance based career advancement
About Cognologix:
Cognologix helps companies disrupt by reimagining their business models and innovate like a Startup. We are at the forefront of digital disruption and take a business-first approach to help meet our client’s strategic goals.
We are a Data focused organization helping our clients to deliver their next generation of products in the most efficient, modern, and cloud-native way.