Senior Machine Learning Engineer

Engineer Responsible AI for the HR and PEO Services Industry

Smarter HR operations begin with machine learning that is accurate, responsible, and ready for production. The Senior Machine Learning Engineer transforms complex business needs into scalable AI solutions across payroll, benefits, workforce, and client services. Your expertise will guide high-impact decisions while advancing a long-term global career with Emapta, designed for top 1% talent seeking purpose, influence, and exceptional growth.

Snapshot

• Employment Type: Indefinite-Term Contract
• Work Setup: Work From Home/Remote
• Shift: Day Shift, Weekends Off

Benefits

• 5-day work week
• Weekends off
• Work-from-home arrangement
• 20 vacation days in total
• Prepaid medicine
• Fully customized Emapta laptop and peripherals
• Direct exposure to global clients
• Career growth opportunities
• Diverse, inclusive, and supportive work environment where every individual is respected, valued, and empowered to succeed
• Prime office locations in Bogotá and Medellín
• Unlimited upskilling through Emapta Academy courses (Want to know more? Visit https://emapta.com/training-calendar/)

Qualifications

Education

• High school diploma or equivalent required
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field preferred
• Advanced quantitative degree or an equivalent combination of education, training, and relevant experience considered

Skills and Experience

• 3-5 years of experience in machine learning, applied data science, or a related field, including deploying and maintaining production models or AI systems
• Proven ownership of the modeling lifecycle, from problem framing and data exploration to evaluation, deployment, monitoring, and retirement
• Advanced Python proficiency using pandas, scikit-learn, and a deep learning or transformer library
• Strong SQL skills and production experience with Snowflake, Snowpark, or a comparable cloud data platform
• Expertise in model evaluation, including metric selection, baselines, cross-validation, leakage detection, calibration, and error analysis
• Experience building and evaluating LLM applications using prompt design, structured outputs, embeddings, vector search, retrieval-augmented generation, and tool use
• Knowledge of forecasting, time-series analysis, natural language processing, or document-understanding methods
• Familiarity with model fairness, disparate-impact analysis, and responsible AI practices for employment, compensation, or benefits use cases
• Experience collaborating with MLOps or platform engineers on deployment, monitoring, continuous integration, and cost management
• Ability to provide technical direction, review engineering work, manage competing priorities, and explain model limitations to nontechnical audiences
• Sound judgment in handling sensitive and regulated data and escalating privacy, security, or compliance risks
• Experience in PEO, HR technology, payroll, benefits, insurance, or another regulated data environment strongly preferred

Computer Skills

• Proficiency in Microsoft Office, Python, SQL, Snowflake, Git, containers, continuous integration, and experiment-tracking or model-registry platforms
• Familiarity with MLflow, Weights & Biases, Snowflake Cortex, Amazon Bedrock or SageMaker, Anthropic Claude API, dbt, Docker, vector search, Power BI, Tableau, Sigma, Jira, or Confluence preferred

Certifications and Licenses

• SnowPro Advanced, AWS Certified Machine Learning Engineer, or an equivalent certification considered an advantage

Responsibilities

Essential Duties

• Translate business needs into machine learning or AI problems and recommend modeling, business rules, process changes, or no technical solution based on expected value
• Select classical machine learning, forecasting, NLP, or LLM techniques while balancing accuracy, interpretability, latency, cost, and maintainability
• Build feature engineering, training, and inference logic in Snowflake and Python with data engineering and AI/MLOps teams
• Own model evaluation and experimentation, including datasets, metrics, baselines, calibration, error analysis, statistical significance, guardrails, and release criteria
• Design LLM solutions using prompting, retrieval-augmented generation, tool use, agentic orchestration, and fine-tuning with technologies such as Anthropic Claude, Snowflake Cortex, and Amazon Bedrock
• Develop evaluation frameworks for generative and agentic systems using golden datasets, regression suites, hallucination and refusal checks, adversarial and prompt-injection testing, and human review
• Create predictive and forecasting models for turnover, retention, benefits utilization, renewal costs, workers' compensation claims, payroll anomalies, staffing demand, and client health
• Build document and language models for classification, extraction, summarization, and routing while defining accuracy thresholds and exception-handling procedures
• Assess model fairness, disparate impact, stability, and human-oversight requirements and recommend remediation, restricted use, or non-deployment when necessary
• Maintain model documentation for monitoring, retraining, internal audits, client due diligence, and regulatory inquiries
• Monitor production performance, drift, and errors and direct retraining, recalibration, scope reduction, or retirement
• Partner with product, software development, Legal, and Information Security teams to define feasible AI features and address privacy, security, regulatory, and automated-employment requirements
• Evaluate emerging technologies and vendors based on business value, performance, feasibility, compliance, security, and cost
• Mentor machine learning, AI/MLOps, and data engineers and review designs and code for production readiness
• Resolve production model-quality issues through root-cause analysis, risk prioritization, and cross-functional corrective action
• Plan initiatives and communicate scope, dependencies, timelines, uncertainty, and risks to stakeholders

Other Duties

• Participate in a business-hours support rotation for AI and machine learning services
• Maintain technical expertise through training, research, workshops, and continued professional development
• Improve modeling standards, evaluation practices, documentation, and shared tools
• Support special projects, process improvements, team objectives, and other assigned duties

Competencies

• Communicate clearly, build consensus, and handle sensitive information with discretion
• Establish trust through honesty, professionalism, empathy, and respect
• Resolve operational and interpersonal challenges through sound analysis and timely action
• Demonstrate accountability, honor commitments, protect confidential information, and learn from mistakes
• Build effective stakeholder relationships and consistently address client needs

About the Client

Our client is a nationally recognized U.S. professional employer organization with nearly three decades of success helping businesses grow, scale, and strengthen their workforces. Ranked among the country's ten largest PEO firms, it has earned repeated distinctions for rapid growth, workplace excellence, leadership, diversity, and employee well-being. Its comprehensive payroll, benefits, compliance, risk management, and HR solutions are backed by responsive specialists and exceptional customer satisfaction, enabling organizations to improve performance while creating better employee experiences at every growth stage.

Join the Top 1% Talent. A Better Career. A Better Life.

The world doesn't move forward because everyone is the same. It moves forward because people bring different perspectives, strengths, and ways of thinking. If you've been waiting for a workplace that sees your potential before anything else, this is your moment.

At Emapta Colombia, we believe great careers begin when people are recognized for what they can do-not defined by what others expect. That's why we're creating more opportunities for exceptional talent to thrive in an inclusive workplace where your skills are valued, your ambitions are supported, and your contributions make a lasting impact.

Since 2010, Emapta has helped transform global outsourcing through personalized solutions and seamless collaboration. Today, we're proud to support more than 1,200 clients worldwide with a community of over 12,000 talented professionals-all united by one belief: exceptional talent can come from anywhere.

Apply today and let your talent take the lead. The future of work needs people like you.

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