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Senior SW Engineer

Job Description - Senior SW Engineer

Description
We are looking for a talented and experienced Applied R&D Engineer to join our innovative team. In this role, you will have the opportunity to work on a diverse range of projects, utilizing your expertise in AI, Machine Learning, and MLOps. Your contributions will be vital in driving our company's success and shaping the future of our AI-powered solutions.

Responsibilities
  • Design and implement AI models, leveraging your expertise in AI/ML algorithms and frameworks.
  • Collaborate with stakeholders and engineers to operationalize ML models, ensuring efficient and effective deployment.
  • Develop and maintain CI/CD pipelines for ML workflows, optimizing the model training and evaluation process.
  • Utilize your understanding of RAG, neural networks, and other AI/ML concepts to enhance model performance.
  • Work closely with customers to understand their needs and deliver tailored ML solutions.
  • Stay updated with the latest advancements in AI and MLOps, ensuring our company remains at the forefront of technology.
  • Provide technical guidance and mentorship to junior team members, fostering a culture of knowledge sharing.
  • Ensure data security and privacy compliance in all ML projects, adhering to industry best practices.
  • Collaborate with cross-functional teams to integrate ML models into existing systems and processes.


Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 8+ years of experience in AI/ML development, including hands-on experience with MLOps tools and serving frameworks, such as Mlflow, n8n, flyte ,TorchServe, etc for model deployment, and Model Context Protocol for Agentic AI Tools.
  • Proficiency in programming languages such as Python, Java, and TypeScript, with a strong understanding of software development principles.
  • Expertise in data handling, particularly SQL, for efficient data management and analysis.
  • Experience with MLOps tools and serving frameworks, such as TensorFlow Serving and TorchServe, for model deployment.
  • Strong background in model engineering and improvement, with a track record of successful model deployment and productionalization.
  • Familiarity with Natural Language Processing (NLP), LLMs and its applications in AI/ML projects.
  • Understanding of CI/CD practices and the ability to develop and maintain pipelines for ML workflows.
  • Excellent problem-solving and analytical skills, with a proactive approach to identifying and resolving technical challenges.
  • Strong communication and collaboration skills, with the ability to work effectively in a dynamic team environment.


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