Machine Learning Ops Lead at Keller Executive Search

, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

26 Jan, 26

Salary

145000.0

Posted On

28 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI, Data Analysis, Cross-Functional Coordination, Process Ownership, Analytical Skills, Communication Skills, Vendor Management, Singapore Market Knowledge, OKRs, Spreadsheets, BI Tools, Leadership, Project Management, Safety Standards, ROI Analysis

Industry

Staffing and Recruiting

Description

This is a position within Keller Executive Search and not with one of its clients. As the Machine Learning Ops Lead in Singapore, Singapore, this mid‑level role contributes to ai and innovation execution while collaborating with senior leaders. The position focuses on scalable processes, measurable outcomes, and cross‑functional coordination to support growth in Singapore and the region. Key Responsibilities: - Pilot practical AI use cases with clear safety, effectiveness, and ROI criteria. - Translate quarterly goals into clear plans, cadences, and dashboards. - Use data to diagnose issues, prioritize work, and track outcomes against OKRs. - Coordinate with Sales, Marketing, IT, Finance, and People Operations to unblock execution. - Own day‑to‑day vendor interactions and support compliant, efficient processes. - Prepare succinct updates and materials for leadership reviews. - 3–6 years of relevant experience with increasing scope; experience working in cross‑functional teams. - Evidence of process ownership and delivery against targets/OKRs. - Strong analytical skills; proficiency with spreadsheets and BI/reporting tools. - Clear written and verbal communication, including executive‑ready materials. - Working knowledge of Singapore market practices and applicable standards. - Bachelor’s degree or equivalent practical experience; relevant certifications are a plus. Competitive compensation: S$ 118,000–145,000 SGD Opportunities for professional growth and leadership development. Company culture: Flat management structure with direct access to decision‑makers; open communication environment. Full medical coverage. Equal Employment Opportunity Statement: Keller Executive Search provides equal employment opportunities to all qualified applicants and employees. Employment decisions are based on merit, qualifications, and business needs, without regard to protected characteristics under applicable law. Commitment to Diversity: An inclusive and equitable workplace is actively fostered. Hiring, development, and advancement practices are designed to broaden representation and ensure fair access to opportunity. Data Protection and Privacy: Personal data is processed solely for recruitment and employment purposes, in accordance with applicable data‑protection laws (including GDPR where relevant). Information may be retained for compliance and legitimate interests, subject to data minimization and security controls. Pay Equity: Compensation practices are reviewed to support pay equity for substantially similar work, accounting for bona fide factors such as experience, education, and performance. Health and Safety: Workplace health and safety obligations are observed in line with applicable national and local requirements. Employees are expected to follow all safety policies and promptly report hazards. Compliance with Law: All recruitment, selection, and employment practices are conducted in compliance with applicable laws and regulations in the jurisdiction of employment. Note: This job posting may be for a position with Keller Executive Search or one of our clients. The specific employer will be identified during the application and interview process. Employment laws and requirements may vary depending on the employer and location.

Responsibilities

The Machine Learning Ops Lead will pilot practical AI use cases and translate quarterly goals into actionable plans. This role involves coordinating with various departments to ensure effective execution and tracking of outcomes against objectives.