About Us
Systango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web & enterprise development, mobile apps, QA and DevOps. Ulster University, Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, Possible and we do it literally.
About The Role
We are seeking an
AI/ML Lead with strong expertise in
advanced machine learning, deep learning architectures, and Generative AI to design and deliver scalable, production-grade AI solutions. This role demands hands-on technical depth, architectural thinking, and the ability to guide teams while working closely with business and product stakeholders.
The ideal candidate has proven experience across
ML model development, GenAI inference/training, API deployment, and
model evaluation, with exposure to real-world applications in domains such as
NLP, Computer Vision, or Recommendation Systems.
Key Responsibilities
- Lead the end-to-end lifecycle of AI/ML solutions, from problem formulation and model development to deployment and monitoring.
- Design and implement advanced ML techniques, including ensemble methods, reinforcement learning, and classical ML algorithms.
- Develop and optimize deep learning models using architectures such as Transformers, GANs, and LSTMs.
- Apply AI/ML solutions across specialized domains such as NLP, Computer Vision, and Recommendation Systems, based on business needs.
- Build and deploy scalable RESTful APIs using Django, Flask, or FastAPI for model inference and integration.
- Perform rigorous model evaluation, including cross-validation, hyperparameter tuning, and selection of appropriate performance metrics.
- Drive Generative AI initiatives, leveraging LLM APIs for inference and contributing to LLM fine-tuning, training, and deployment (where applicable).
- Collaborate closely with data engineering teams to ensure data quality, feature readiness, and efficient pipelines.
- Document solution architectures, model assumptions, workflows, and deployment strategies.
- Mentor and guide junior engineers, while providing technical leadership across AI initiatives.
Required Skills & Qualifications
- 69 years of hands-on experience in Machine Learning, Deep Learning, and AI systems.
- Strong proficiency in Python, with solid software engineering and OOP practices.
- In-depth knowledge of deep learning architectures (Transformers, GANs, LSTMs) and advanced ML techniques.
- Hands-on experience with Scikit-learn, Pandas, NumPy, and TensorFlow-Keras or PyTorch.
- Strong understanding of model evaluation, including cross-validation, hyperparameter tuning, and performance metrics.
- Practical experience with Generative AI models, including LLM API-based inference.
- Experience building and deploying REST APIs using Django, Flask, or FastAPI.
- Familiarity with SQL and NoSQL databases.
- Proficient with Git/GitHub and collaborative development workflows.
- Strong communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Preferred / Good-to-Have Skills
- Experience with LLM training, fine-tuning, and deployment pipelines.
- Exposure to MLOps tools such as MLflow, Kubeflow, or Weights & Biases.
- Experience with Big Data technologies (Spark, Hadoop).
- Cloud exposure (AWS, GCP, or Azure) for AI/ML workloads.
- Relevant AI/ML or cloud certifications.
Why Join Us
- Work on cutting-edge AI and Generative AI solutions with real-world impact.
- Lead high-visibility, innovation-driven AI initiatives.
- Collaborate with strong engineering, product, and data teams.
- Global exposure, learning opportunities, and a performance-driven growth culture.
