Most Loved Workplace® Certified JobInformation Security Specialist (Endpoint Protection)
Most Loved Workplace® Certified JobAbout the Role
At NETSOL Technologies Inc., a Most Loved Workplace® certified employer in the Technology space, Empowering Global Businesses with Enterprise Solutions Since 1996.
At NETSOL Technologies, we are a leading global provider of software solutions, delivering innovative products and services to help businesses around the world achieve digital transformation. We’re proud to be at the forefront of creating next-generation technology solutions in industries like automotive, finance, and more. As we continue to grow and innovate, we’re looking for a talented AI / ML Engineer to join our Scientific Computing team. You will have the opportunity to make a significant impact, working on projects that influence how users interact with cutting-edge applications and platforms. If you’re passionate about AI/ML, eager to collaborate with talented professionals, and ready to take your career to the next level, NETSOL Technologies is the place for you. We are assembling a cutting-edge AI team to build a revolutionary product. We seek an exceptionally talented and self-motivated Senior AI/ML Engineer with a robust foundation in both machine learning theory and core software engineering. This role demands an individual who not only excels in developing and deploying advanced ML models—including generative AI and large language models (LLMs)—but also possesses strong engineering acumen to create scalable, maintainable, and production-grade systems. As a key member of our startup, you will work collaboratively across teams to translate complex business KPIs into technical solutions, while continuously pushing the boundaries of AI innovation.
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Requirements
- Bachelor’s degree in Computer Science (mandatory).
- Master’s degree or PhD from a reputed institution is highly preferred.
- 2-4 years of relevant experience in machine learning, data science, or software engineering.
- Proven track record in building and deploying machine learning systems in production environments.
- Authored or co-authored publications for top-tier conferences (e.g., EMNLP, CVPR).
- Deep theoretical knowledge in statistics, machine learning algorithms, and deep learning.
- Proficiency in Python and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch) as well as big data tools like Spark or Databricks.
- Solid software engineering skills including RESTful API development, containerization (Docker), and experience with event-driven architectures.
- Experience designing, integrating, or supervising CI/CD pipelines and model versioning systems.
- Understanding of modern orchestration tools and agent patterns for AI systems.
- Exceptional self-motivation, adaptability, and a strong drive for continuous learning and innovation.
- Excellent communication and collaboration skills, with the ability to translate technical insights for diverse audiences.
- Ability to thrive in a fast-paced, high-pressure startup environment with long hours and open-ended problem-solving challenges.
- Hands-on experience with generative AI models and designing GPT-like architectures.
- Familiarity with additional programming languages (e.g., Java, Rust) and cloud-based ML platforms.
- Demonstrated ability to read and contribute to academic research or conference publications.
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