Description
Must Haves:
Minimum Relevant Experience: 4-5 Years AI/ML
- ML: Algorithms
- Model Ops: Deployment, Monitoring, Versioning
- Data Engineering: ETL, FastAPI, Pipeline Development
- Tooling Proficiency: Docker, Kubernetes, MLflow
- Frameworks: Scikit-learn, TensorFlow, PyTorch
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Joining time / Notice Period: Less than 15 Days, Immediate Preferred
MUST be from Product Based organization.
Requires 5 Days WFO - HSR Layout, Bangalore (4 Days WFH is given in a month as per the policy)
Interview Process - 1 Technical Round + Project Round + Managerial Round + CEO Round + HR Round.
About the company:
Location: - Bangalore (Started in 2015, headquartered in Singapore)
Team Strength- 150+ people
About the Company: Neutrinos is a technology company that automates business processes for insurance enterprises. The Neutrinos AI-infused intelligent automation platform includes everything needed to design, automate, and optimize complex processes end to end. Our holistic insurance expertise, intelligent automation platform, and pre-built accelerators, help leading insurers accelerate their enterprise reinvention across underwriting, claims, and distribution – resulting in faster growth and superior Omni-channel experiences.
About the position:
Designation: Software Project Manager (Insurance Domain)
Experience required- 5-8 years.
Reporting To: CEO
Vacancy: 1
Work Mode- work from the office. Frequent International travel involved
JD-
A fast-growing global provider of SaaS-based enterprise low code application development platform.
Role:
Machine Learning EngineerLocation: Bangalore office (preferable)
Experience Level: 5+ years
- Fundamental knowledge of supervise and unsupervised learning and their applications inreal world business scenarios.
- Familiarity with End-2-End Machine Learning model development life cycle.
- Experience in creating data processing pipelines and API development (Fast API).
- Experience with deploying and maintaining ML/DL models in production,model monitoring, and knowledge of concept/data drift, modelreproducibility, code, model, and data versioning.
- Experience with SQL and NoSQL, MLflow, GitHub, docker, Kubernetes, ELK, or similar stack.
- Hands on with text and image processing: cleaning, transformations, and data preparationfor modelling. And should be comfortable with libraries like Pandas, NumPy, OpenCV, PIL, Spacy, transformers etc.
- Should have working knowledge of machine learning frameworks like Scikit[1]learn, PyTorch/ Tensorflow/Keras.
- Experience with cloud computing platforms like GCP and AWS.
- Should understand LLMs, Open AI API, model fine-tuning and prompt engineering.
- Exposure to CI/CD principles and associated tools.
Good to have:
- Experience with deep learning frameworks
- Strong experience in programming and statistics
- Excellent verbal and written communication skills
- Highly developed attention to detail? Strong presentation skills
- Ability to work well in a team environment
- Excellent problem-solving skill