Lead AI Engineer / Data Scientist - USA

Cogniify, Inc.; Santa Clara (CA); Hybrid; USD 150,000 - 170,000; Full time

Benefits offered by this job

Unlimited PTO

Parental leave

Entrepreneurial culture

Open communication

Small teams, big impact

Health benefits

Employee stock purchase program

Team building events

Mentorship

Job summary

Cogniify, Inc. is seeking a Mid-Level AI/ML Engineer to design, build, and deploy machine learning models and end-to-end pipelines that drive business value.

You will own ML solutions from experimentation to production deployment and collaborate with cross‑functional teams to mature MLOps practices. The role emphasizes practical ML engineering, independence in technical decisions, and contributing to scalable ML systems.

Qualifications

• Bachelor’s or Master’s degree in a technical field.
• 3–5 years of professional ML engineering or closely related experience.
• Strong Python skills and hands-on experience with ML frameworks (TF, PyTorch, scikit-learn).

Responsibilities

• Design, build, and deploy ML models and end-to-end pipelines.
• Develop and maintain production ML pipelines (data ingestion, feature engineering, training, validation, serving).
• Implement MLOps, experiment tracking, versioning, and reproducibility.
• Deploy models to production with Docker/Kubernetes and cloud services.
• Monitor production models, detect data drift, retrain workflows.
• Collaborate with data engineers, software engineers, and product teams.
• Optimize model performance for latency and resource efficiency.
• Write production-grade code with tests, logging, and docs.
• Participate in architectural discussions for ML systems.
• Mentor junior engineers and share knowledge.

Skills

Python

TensorFlow

PyTorch

scikit-learn

SQL

Docker

Kubernetes

MLflow

Kubeflow

Airflow

REST APIs

CI/CD

Education

Bachelor’s degree in Computer Science / Mathematics / Statistics / Data Science

Master’s degree in a related technical field

Tools

MLflow

Kubeflow

Airflow

Docker

Kubernetes

Spark

dbt

Feast

Tecton

DVC

LakeFS

Job description

About the Role

We are seeking a Mid-Level AI/ML Engineer to design, build, and deploy machine learning models and end-to-end ML pipelines that drive business value. In this role, you will independently own the development of ML solutions from experimentation through production deployment, collaborate with cross-functional teams, and contribute to the maturity of our MLOps practices. The ideal candidate combines strong ML fundamentals with practical engineering skills and a growing ability to make independent technical decisions.

Key Responsibilities

Design, develop, and deploy machine learning models for classification, regression, NLP, computer vision, or recommendation use cases.

Build and maintain end-to-end ML pipelines including data ingestion, feature engineering, model training, validation, and serving.

Implement MLOps practices including automated training pipelines, experiment tracking, model versioning, and reproducibility.

Deploy models to production using containerization (Docker, Kubernetes) and cloud-native services.

Monitor model performance in production, implement data drift detection, and manage model retraining workflows.

Collaborate with data engineers, software engineers, and product teams to integrate ML solutions into applications and services.

Optimize model performance for latency, throughput, and resource efficiency in production environments.

Write production-quality code with proper testing, logging, error handling, and documentation.

Participate in technical design discussions and contribute to architectural decisions for ML systems.

Mentor junior engineers and contribute to team knowledge-sharing and best practices.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or a related technical field.

3–5 years of professional experience in machine learning engineering, applied ML, or a closely related role.

Strong proficiency in Python and 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 practices including MLflow, Kubeflow, Airflow, or similar orchestration frameworks.

Experience with cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) for training, deployment, and serving.

Proficiency in SQL and experience working 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 techniques.

Familiarity with REST APIs and microservices architecture for model serving.

Preferred Qualifications

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, or 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.

Salary Range

US East/West Coast: $150,000 - $170,000

Disclaimer: Actual compensation may vary based on individual qualifications, experience, and specific geographic location. These figures represent base salary ranges and do not include additional benefits or incentives.

Perks And Benefits Of Working With Us

Unlimited PTO.

Please ask us about our very generous parental leave, much above industry standards!.

Entrepreneurial culture where pushing limits and taking risks is everyday business.

Open communication with management and company leadership.

Small, dynamic teams = massive impact.

Medical, Dental and Vision coverage for employees.

Access to Disability & Life insurance.

Mental health and wellbeing support

Employer Stock Purchase Program (ESPP)

Yearly Team building experiences

Mentorship and sponsorship opportunities

Manager resources and support

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.