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Jr/mid/sr Ai Engineer
2 weeks ago
**Top 3 reasons to join us**:
- Working in one of the Best Places to Work
- Hybrid working and Flexible working hours
- 13th-month salary and Performance bonus
**Job description**:
** Key Responsibilities**
** AI ENGINEER**
- Work closely as a project team as the main contributor in the entire lifecycle of data science projects, from gathering business requirements to solution delivery, and deliver project outcomes to internal stakeholders or external customers.
- Engages with clients to understand business needs, present findings, and align technical work with stakeholder goals.
- Provides structured feedback to junior members, supports onboarding, and contributes to skill-building within the project team.
- Developing scalable AI systems and designing/building algorithms that automate predictive data models.
- Creating and managing the AI development and production infrastructure, including automating AI infrastructures for data science teams.
- Participating in all phases of AI solutions development, from requirements definition and design to development, deployment, integration, maintenance, performance tuning, and monitoring.
- Collaborating extensively with cross-functional teams, including data scientists, software engineers, and product managers, to define project requirements, ensure seamless progress, and facilitate AI adoption and best practices.
- Driving scalability improvements and introducing new capabilities in machine learning platforms, often working across the full stack on tools and infrastructure that empower machine learning teams.
** DATA SCIENTIST**
- Work closely as a project team to lead in the entire lifecycle of data science projects, from gathering business requirements to solution delivery, and deliver project outcomes to internal stakeholders or external customers.
- Engages with clients to understand business needs, present findings, and align technical work with stakeholder goals.
- Owns planning of assigned modules, contributes to task breakdown, estimation, and milestone alignment, and supports backlog grooming discussions.
- Leads development of a complete module or sub-system (e.g., full model training pipeline or certain solution direction). Can propose solution design, test, and iterate independently. Coordinates with project lead to align with project needs.
- Proactively explores and evaluates new tools or methods relevant to the problem domain and integrates them into module-level components with mínimal supervision.
- Provides structured feedback to junior members, supports onboarding, and contributes to skill-building within the project team.
- Proactive in contributing to the growth of internal capabilities (e.g., training, knowledge-sharing, framework design).
**Your skills and experience**:
** Required Skills & Qualifications**
** AI ENGINEER**
- A Bachelor's degree in a technical field such as CS, AI, or Data Science, or equivalent practical experience. A Master’s degree is a plus.
- **2- 3 years of professional experience building and shipping software, with a focus on AI/ML systems.**
- Familiarity with cloud platforms (AWS, Azure, GCP).
- Proficiency with containerization (Docker, Kubernetes) and modern CI/CD practices for production environments.
- **Experience in building or prototyping features with GenAI capabilities (LLMs, Embeddings, Fine-Tuning) and core NLP concepts.**
- **Fluent in English with strong communication skills,** especially when engaging with non-technical business stakeholders.
- The ability to work independently, troubleshoot complex issues, and mentor more junior team members is also expected.
- Strong problem-solving skills and a data-driven mindset are fundamental.
- Develop and Implement Evaluation Frameworks: The engineer will be responsible for creating and deploying frameworks to test and benchmark generative AI solutions for both quantitative and qualitative metrics
- Experience with high-performance computing, GPU optimization, and building for low-latency environments is a strong plus.
** DATA SCIENTIST**
- Bachelor’s degree in Mathematics, Statistics, Data Science, Computer Science, AI, Engineering, or a highly related field is required. A Master’s degree in any of the above disciplines is preferred.
- Have **at least 3 years** and above of experience in one or more data science domains such as **machine learning, deep learning, natural language processing (NLP), computer vision (CV), optimization, or statistics.**
- Proven experience leading data science workstreams or small projects, and mentoring junior data scientists.
- **Fluent in English with strong communication skills**, especially when engaging with non-technical business stakeholders.
- Experience with MLOps tools and practices (e.g., model packaging, CI/CD for ML, model monitoring, ML pipelines).
- High proficiency in Python and SQL, along with relevant data science libraries
- Hands-on experience with cloud platforms (e.g., GCP, AWS, Azure) and container