Senior Machine Learning Engineer – Contract

This is a fully remote position, open to applicants in Pakistan.

📋 Description

• Refactor, modernize, and productionize existing machine learning models and Applied AI capabilities, including natural language processing and generative AI solutions.

• Develop new machine learning components and re-engineer existing models into standardized, production-ready modular parts.

• Create production machine learning applications and supporting services primarily utilizing Python.

• Establish and maintain dependable machine learning pipelines for model integration, evaluation, deployment, and operation.

• Engineer robust machine learning workflows featuring retry logic, error handling, and reproducible execution.

• Design and automate model evaluation pipelines using golden datasets alongside quality and performance thresholds.

• Assess generative AI, classification, and other machine learning models using relevant metrics.

• Implement guardrails and evaluation mechanisms for grounding, hallucinations, and the quality of generative AI outputs.

• Apply Applied AI techniques, including Retrieval-Augmented Generation (RAG).

• Design mechanisms for model, prompt, and input-data provenance to ensure auditability and reproducibility.

• Build infrastructure for shadow testing, A/B testing, fallback strategies, and kill switches.

• Assist in labeling, curation, and the ongoing development of golden datasets.

• Create human-in-the-loop feedback pipelines to capture reviews and corrections.

• Integrate third-party AI APIs and construct adapter/API interfaces.

• Implement observability and telemetry to monitor model behavior, errors, compute costs, token usage, and latency.

• Contribute backend engineering efforts to integrate machine learning components into the broader application.

• Support both batch and real-time machine learning workloads.

⛳️ Requirements

• Over 6 years of professional experience in AI/Machine Learning, with authentic production experience.

• More than 5 years of professional experience in MLOps.

• At least 2 years of real Applied AI experience beyond experimentation or personal projects.

• Strong professional proficiency in Python.

• Proven track record in productionizing and deploying AI/ML applications and models.

• In-depth understanding of Applied AI/ML and MLOps principles.

• Significant hands-on experience with model evaluation and establishing quality/performance criteria.

• Experience with generative AI and large language models (LLMs), including grounding and hallucination evaluation.

• Practical understanding of RAG and other Applied AI techniques.

• Experience in building and operating machine learning pipelines and production ML architectures.

• Experience in designing reliable machine learning workflows with error handling, retry mechanisms, and repeatable execution.

• Familiarity with golden datasets for model evaluation and quality gating processes.

• Experience in building observable machine learning systems utilizing logging, monitoring, and telemetry.

• Understanding of model/data provenance and principles of auditability and reproducibility.

• Experience in implementing safe production deployment practices, including testing, fallback, or fail-safe mechanisms.

• Adequate backend engineering experience to build APIs, integrations, and production-ready services around machine learning capabilities.

• Experience in addressing real production machine learning challenges involving reliability, deployment, integration, evaluation, or performance.

• Familiarity with governance, compliance, and safeguards for sensitive data and AI-generated outputs.

• Nice to have: Experience with FastAPI.

• Nice to have: Familiarity with Argo Workflows or similar DAG-based orchestration frameworks.

• Nice to have: Knowledge of Docker and Kubernetes.

• Nice to have: Experience with AWS, Azure, or GCP.

• Nice to have: Experience in multi-cloud or cloud-agnostic applications.

• Nice to have: Proficiency in TypeScript and/or Go.

• Nice to have: Experience with speech-to-text or transcription models.

• Nice to have: Experience in developing real-time machine learning applications.

• Nice to have: Familiarity with traditional NLP models, transformer-based models, encoders, and decoders.

• Nice to have: Experience with external model/provider integrations such as OpenAI or Claude.

🏝️ Benefits

• Flexible remote work arrangement.

• A genuine community dedicated to growth and well-being.

• Long-term employment opportunity.

• Opportunities for both professional and personal development.