Lead Production ML Engineer & Mentor for AI Innovation

TechTwitter.io; Jakarta Pusat; On-site; IDR 180,000,000 - 300,000,000; Full time

Job summary

TechTwitter.io is seeking an experienced Machine Learning Engineer to analyze large datasets, identify patterns, and extract consumer insights. You will lead the design, development, and maintenance of scalable ML architectures and data pipelines.

The ideal candidate has 3–6 years in ML engineering or data science, a proven track record of bringing models to production, and strong problem-solving, communication, and mentoring skills.

Qualifications

• Strong academic background (STEM preferred).
• 3–6 years of experience in ML engineering or data science.
• Proven track record of bringing ML models to production.
• Excellent problem-solving and ability to work independently.
• Comfortable to take ownership over building new data & AI projects.
• Strong communication and teamwork with stakeholders.
• Experience leading and mentoring engineering teams.
• Proficiency in finance and GenAI related projects with proven experience.

Responsibilities

• Analyze large volumes of data, identify patterns and insights useful for consumers.
• Lead the design, development, and maintenance of scalable ML architectures and pipelines.
• Explore new models and improve existing ML models.
• Mentor and guide junior ML engineers, promoting best practices and technical excellence.
• Bring best practices in ML with a scalable tech stack.
• Push to improve Status Quo by researching and adopting cutting-edge AI technology and techniques.
• Collaborate closely with cross-functional teams to align ML solutions with business goals.

Skills

Data science

Machine learning

Leadership

Problem solving

Communication

Teamwork

Ownership

Education

STEM degree

Job description

TechTwitter.io is seeking an experienced Machine Learning Engineer to analyze large datasets, identify patterns, and extract consumer insights. You will lead the design, development, and maintenance of scalable ML architectures and data pipelines.

The ideal candidate has 3–6 years in ML engineering or data science, a proven track record of bringing models to production, and strong problem-solving, communication, and mentoring skills.