Synapsewerx is seeking a highly skilled and experienced Senior Data Scientist / AI Agent Engineer with significant experience in building, training and tuning Models and a solid foundation in Generative AI Models, Machine Learning, Deep learning, Statistical Modelling, NLP, Neural Networks and Computer Vision. The ideal candidate will bring a wealth of knowledge and experience from working within recognised enterprise organisations, having contributed to large-scale data projects. This role is pivotal in guiding our clients through their AI transformation journey, delivering exceptional solution architectures and implementing solutions that deliver real-world business benefits.
Key Responsibilities
- Lead the design, development, and deployment of machine learning models, with a strong emphasis on generative AI and autonomous agent capabilities.
- Architect, design, and implement scalable machine learning systems and pipelines for both real-time and batch processing, ensuring high availability, optimal performance, and system reliability.
- Develop and productionise machine learning models, including deep learning, statistical models, and advanced algorithms, applying best practices in software engineering. This includes building data preparation and processing pipelines, improving service performance, and enhancing system reliability.
- Utilise generative AI techniques and autonomous agent frameworks to develop intelligent systems capable of autonomous decision-making and task execution.
- Promote MLOps practices within the organisation, streamlining model deployment and management processes.
- Demonstrate expertise in cloud platforms, with preference for certifications in AWS, Azure, GCP or Oracle Cloud.
- Conduct thorough testing and validation of machine learning models to ensure their robustness and reliability.
- Stay up to date with emerging technologies and trends, researching state-of-the-art deep learning models, prototyping new ideas, and conducting both offline and online experiments.
- Build custom AI agents using various tools and frameworks tailored to client-specific needs.
- Create and scale proof-of-concept solutions to validate potential AI and data solutions for prospective clients or to improve value propositions.
- Engage with clients to understand their AI and data transformation challenges, providing strategic and customised solutions.
- Establish robust governance, monitoring, and support processes to maintain AI and data solutions in production environments.
- Drive the adoption of best practices in data architecture, including the development of reference architectures, and ensure data privacy and security standards are met.
- Analyse large and complex datasets to derive actionable insights, optimising solutions and overall performance.
- Mentor and guide team members, fostering a culture of continuous learning and development.
- Create comprehensive documentation for data and AI systems, models, and processes.
- Effectively communicate and articulate ideas, identifying risks and challenges based on experience and best practices.
- Continuously stay abreast of industry advancements in data and AI to enhance service offerings.
- Demonstrate excellent proficiency in SQL and Python.
Experience
- A minimum of 5 years of relevant experience in Data applications, with a broad exposure to various data architectures, technologies, and principles.
- 3+ years of experience in AI/ML engineering in various industry sectors.
- 1-2 years of experience in Generative Systems.
- Preferred experience with platforms such as Databricks, AWS (SageMaker / Bedrock), GCP, Azure, with a focus on scalability, performance, and strong security.
- A passion for continuous learning and professional development, aligned with Synapsewerx's values of innovation and community.
Skills (Essential):
- Proficiency in programming languages such as Python, R, and Java for developing AI algorithms and applications
- Strong foundation in mathematics and statistics for understanding and developing machine learning models
- Familiarity with various machine learning algorithms and frameworks (e.g., TensorFlow and PyTorch).
- Data analysis and manipulation skills such as data wrangling, cleaning and exploration using tools such as Pandas, NumPy, and SQL
- Understanding and exposure to Deep Learning - neural networks, architectures (CNNs, RNNs, GANs, LSTM) - and Natural Language Processing.
- Strong analytical and critical thinking abilities to approach complex business problems and develop innovative solutions
- Awareness on ethics and AI governance; considerations and implications of AI technologies including bias, privacy, and accountability
Skills (Desirable):
- Cloud Computing skills with various cloud platforms (AWS, Google Cloud, or Azure) for deploying AI models, leveraging AI/Data services, and handling large datasets
- Implementation background on data integration and APIs using various platforms such as Boomi, MuleSoft, WSO2
- Skills in enterprise platforms such as Salesforce, ServiceNow for configuration and enablement of its AI agent / Data features
- Familiarity with container orchestration such as Kubernetes
Qualifications
Whilst we place a focus on real-world and referenceable experience, we also highly value vendor certifications. As such, we hold any of the following certifications in high regard:
- Data and AI specialized Certifications (i.e., Generative AI, Machine Learning, Deep Learning)
- AI and Data Relevant Cloud Certifications (AWS, GCP, and Azure)
- Databricks Certifications, including Data Engineer, ML Engineer, Gen Ai Engineer
- Salesforce Data and AI Certifications
- ServiceNow Now Assist Certifications
- TOGAF Certification
- Boomi and MuleSoft Integration Platform Certifications
