SR Software Systems Engineer-9366-Machine Learning

Position: Sr Software Systems Engineer-Machine Learning
Experience: 4 to 10 Years
Location: Remote/Bangalore
Job Responsibilities:
Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation.
Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy and participate hands-on in design reviews, code reviews, and implementation.
Craft high-performance, production-ready machine learning code for our next-generation real-time ML platform. Extend existing ML libraries and frameworks.
Working closely with other engineers and scientists, lead solutions to accelerate model development, validation and experimentation cycles, and integrate models and algorithms in production systems at a very large scale.
Mentor and develop other engineers on the team, establish technical direction and foster team culture.
Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.
Basic Qualifications:
Degree in mathematics/computer science or related discipline.
4+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
4+ years of experience in programming, with proficiency in at least one programming language, preferably Python or Java.
3+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
Experience working with distributed data and ML technologies (e.g. MapReduce, Spark, Flink, Kafka, PySpark, SageMaker etc.).
Experience as a mentor, tech lead or leading an engineering team.
Adept at tackling highly complex, ambiguous or undefined problems.
Preferred Qualifications:
MS or PhD in Computer Science or equivalent experience in ML.
Experience dealing with real-world large-scale datasets.
Prior experience delivering end-to-end ML solutions, including data preparation, training, fine-tuning and deployment of large models.
Prior experience in developing ML optimization techniques in frameworks like PyTorch and CUDA.