Overview
This person will partner closely with the Sales Data Science Capabilities team to support the development, maintenance, monitoring, and continuous improvement of AI/ML models and LLM-enabled applications. The role is highly execution-oriented and will focus on translating business and data science requirements into scalable, reliable, and well-monitored model solutions. The ideal candidate is a strong hands-on practitioner with experience developing machine learning models, working with large-scale data, building model pipelines, monitoring model performance, and supporting production ML systems.
Responsibilities
Develop, enhance, and maintain AI/ML models that support Sales use cases such as lead scoring, product recommendation, seller prioritization, customer segmentation, next-best-action, and seller productivity etc.
Support the development of LLM and GenAI-enabled applications, including prompt experimentation, model evaluation, retrieval workflows, and quality measurement.
Partner with the DS capabilities team to translate business problems into model development plans, analytical approaches, and technical implementation.
Build and maintain model training, scoring, validation, and monitoring pipelines in partnership with data engineering and platform teams.
Monitor model performance, data quality, drift, stability, and business impact; proactively identify issues and recommend improvements.
Conduct model refreshes, feature updates, backtesting, performance diagnostics, and enhancement analyses to improve model accuracy and business relevance.
Support experimentation and measurement for AI/ML capabilities by preparing datasets, defining model-level diagnostics, and analyzing treatment/control or pre/post performance where applicable.
Write clean, scalable, and well-documented SQL and Python code for data extraction, feature engineering, modeling, evaluation, and reporting.
Create technical documentation for model logic, assumptions, features, performance metrics, monitoring dashboards, and operational handoff.
Qualifications
Highly proficient with 5+ years of Hands On experience in developing and deploying AI/ML models.
Experience with model monitoring, model refreshes, performance tracking, data quality checks, and production ML maintenance.
Highly proficient in SQL, Python and data story telling.
Experience with developing GenAI and/or LLM models is a plus.
Experience working in Sales, Marketing, Product, Customer Support, Web, Strategy, CRM is a plus.
Strong communication skills, with the ability to explain model performance, risks, and tradeoffs to technical and non-technical partners.
Why Join Cogniify?
At Cogniify, you won't be an invisible cog in a machine. As one of our first recruiters, you will have a real voice in shaping how we hire, who we hire, and what our candidate experience looks like across two continents. You'll work closely with our founders and HR Manager, and your work will have a direct, visible impact on the company every week.
Ownership: Build sourcing strategies for two markets from scratch, your playbook, your results.
Access: Direct line to founders and senior leadership. No bureaucracy.
Growth: As Cogniify scales, so does this role. Opportunity to grow into a full-cycle or senior recruiting position.
Flexibility: Fully remote with flexible working hours to accommodate cross-time-zone collaboration.
Perks And Benefits Of Working With Us
Internet allowance
Laptop
PF
Paid PTO
Annual Bonus
Graduity
Yearly Team building experiences
Mentorship and sponsorship opportunities
Manager resources and support
Life & accidental insurance for additional protection.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.
Skills Required
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Data Science, or related field
- 3-5 years of professional experience in machine learning engineering or applied ML
- Proficiency in Python
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience building and deploying ML pipelines in production environments
- Working knowledge of MLOps tools and orchestration frameworks (MLflow, Kubeflow, Airflow)
- Experience with cloud ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)
- Proficiency in SQL and experience with large-scale datasets
- Experience with Docker, Kubernetes, and CI/CD pipelines for ML workflows
- Solid understanding of model evaluation, hyperparameter tuning, and feature engineering
- Familiarity with REST APIs and microservices architecture for model serving
- Experience with deep learning architectures such as Transformers, CNNs, or RNNs
- Familiarity with feature stores (Feast, Tecton) and data versioning tools (DVC, LakeFS)
- Experience with model monitoring and observability tools (Evidently AI, WhyLabs, Prometheus/Grafana)
- Exposure to distributed training frameworks and GPU-accelerated computing
- Experience with A/B testing and experimentation frameworks for ML models
- Knowledge of data engineering tools such as Spark, Kafka, or dbt
What We Do
Cogniify is a Bay Area-based AI execution firm that designs, builds, and deploys custom AI systems for Fortune 500 and Global 2000 companies. The company helps enterprises move from AI pilots to industrialized impact and enterprise-scale production, utilizing deep expertise in AI, advanced analytics, data engineering, and domain consulting.
