SynapseIndia is a software development company with over 24 years of experience, featuring development offices in India and the USA. We serve clients worldwide, delivering innovative solutions tailored to their needs. Our Noida SEZ office is conveniently located just a 10-minute walk from the nearest metro station.
Why work with us?
- Partnerships with Industry Leaders: We are a Google and Microsoft partner, staffed by certified professionals.
- Global Presence: As a multinational corporation, we have clients and employees across the globe.
- Structured Environment: We follow CMMI Level-5 compliant processes to ensure quality and efficiency.
- Timely Salaries: We have consistently paid salaries on time since our inception.
- Job Stability: Despite market fluctuations, we have not had to lay off employees.
- Work-Life Balance: Enjoy weekends off on the 2nd and last Saturday of every month, with no night shifts.
- Our employees are 100% satisfied, thanks to a culture of trust and growth opportunities.
- Eco-Friendly Workplace: We promote health and well-being with special anti-radiation and energy removal features in our offices.
- We prioritize the job security of all our employees.
- We celebrate all festivals with enthusiasm and joy.
- Yearly Appraisals: Exceptional performers can receive over 100% increments during appraisals.
- We recognize and reward top performers on a monthly basis for their outstanding contributions.
- We provide Accidental and Medical Insurance to our employees.
Who are we looking for?
Designation : Senior Team Lead (Artificial Intelligence)
Experience Range : 5+ years
What is the work?
- Lead the design and development of AI/ML solutions, focusing on scalability, performance, and robustness.
- Mentor and guide a team of developers, data scientists, and engineers.
- Define technical strategies and establish best practices for AI/ML project implementation.
- Develop and maintain Python-based systems and libraries for AI/ML workflows, data processing, and automation.
- Implement high-performance Python scripts for data ingestion, feature engineering, and model deployment.
- Optimize Python code for efficiency, scalability, and maintainability.
- Architect and implement AI-driven chatbots utilizing Azure services (Azure Bot Service, Cognitive Services, etc.) and other cloud platforms.
- Integrate Natural Language Processing (NLP) models to enhance chatbot capabilities, including conversational AI, sentiment analysis, and intent recognition.
- Ensure seamless deployment, monitoring, and continuous improvement of chatbot solutions.
- Develop and optimize machine learning models for stock price predictions, derivatives pricing, and market trend analysis.
- Leverage time-series analysis, statistical models, and neural networks to create reliable forecasting tools.
- Collaborate with financial analysts to align models with real-world applications and ensure accuracy.
- Utilize Azure Machine Learning, Databricks, and Synapse Analytics for model training, evaluation, and deployment.
- Implement end-to-end MLOps pipelines for seamless model lifecycle management.
- Ensure cost-effective use of cloud resources while maintaining high availability and performance.
- Work closely with product managers, business analysts, and stakeholders to translate requirements into technical solutions.
- Present technical concepts and project updates to both technical and non-technical audiences.
- Stay abreast of emerging AI/ML technologies, frameworks, and methodologies.
- Drive innovation by experimenting with new tools and techniques to solve complex problems.
What skills and experience are we looking for?
- Python Programming: Extensive experience in Python for AI/ML development, data engineering, and automation.
- Chatbot Development: Expertise in developing and deploying chatbots using Azure Bot Service, Cognitive Services (Speech, Text, and QnA Maker), and other conversational AI tools.
- Azure Cloud: Deep understanding of Azure cloud services, including Azure ML, Azure Databricks, and Azure Kubernetes Service (AKS).
- Machine Learning: Proven experience in applying ML techniques to stock price prediction, derivatives pricing, and portfolio optimization.
- NLP: Strong background in NLP frameworks such as Hugging Face Transformers, spaCy, or OpenAI GPT models.
- Data Engineering: Familiarity with big data tools and frameworks (Spark, Hadoop) and database systems (SQL, NoSQL).
- MLOps: Experience in implementing CI/CD pipelines for ML models using tools like MLflow, Kubeflow, or Azure DevOps.
- Leadership: Proven experience in leading technical teams, managing cross-functional collaborations, and delivering complex projects.
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