Senior SW Engineer

Job 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.