Experience
9 - 12 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Software Engineer
Job Type
ONSITE
Job Description
We are seeking a highly skilled Senior Advanced Software Engineer with strong expertise in Python and AI/ML technologies . The candidate will be responsible for designing, developing, and deploying scalable AI-driven applications and machine learning pipelines , contributing to Honeywell s next-generation intelligent solutions
Core Technical Skills
- Strong programming expertise in Python (3. x) with frameworks like Django/FastAPI.
- Solid understanding of machine learning and deep learning frameworks (TensorFlow / PyTorch / Scikit-learn).
- Hands-on experience in AI/ML model development and deployment .
- Experience with microservices architecture and REST APIs .
- Strong knowledge of cloud platforms (AWS, Azure, or GCP) .
- Familiarity with containerization and orchestration (Docker, Kubernetes) .
- Experience with CI/CD pipelines and DevOps practices .
- Knowledge of data engineering pipelines and feature engineering
- Experience with large datasets, distributed training, and scalable inference systems
- Exposure to GenAI, LLMs, and prompt engineering (preferred)
- Familiarity with MLOps tools and workflows
- Strong understanding of distributed systems and scalable architecture
- Experience with SQL/NoSQL databases (PostgreSQL, MongoDB, etc. )
- 9 12 years of software engineering experience (Python + backend systems).
- Bachelor s or Master s degree in Computer Science / AI / ML / Engineering .
- Proven experience in building and deploying AI/ML solutions in production .
- Architect and develop end-to-end AI/ML pipelines including data ingestion, preprocessing, training, evaluation, and deployment.
- Design and build scalable, cloud-native backend services using Python (Django, FastAPI, etc. ).
- Develop and deploy machine learning models (NLP, computer vision, predictive analytics, or GenAI use cases).
- Implement microservices-based architecture and define APIs for AI-enabled products.
- Drive MLOps practices including CI/CD pipelines, model versioning, monitoring, and retraining.
- Collaborate with data scientists, product managers, and DevOps teams to deliver end-to-end solutions.
- Optimize model performance, inference latency, and scalability for production systems.
- Lead system design discussions and ensure best practices in coding, testing, and documentation.
- Mentor junior engineers and contribute to technical leadership within the team.
- Stay updated with emerging technologies such as Generative AI, LLMs, and Agentic AI frameworks .
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