SADA, An Insight company
Senior Machine Learning Engineer – SADA
As a Senior Machine Learning Engineer at SADA, you will work in a fast‑paced, highly skilled team developing state‑of‑the‑art enterprise solutions on Google Cloud Platform (GCP). You will collaborate with architects and engineers to prototype, build and debug cloud‑native ML and AI solutions around Vertex AI and related technologies.
Responsibilities
Implement end‑to‑end ML solutions for clients, from requirements gathering through model deployment and iterative improvement.
Recommend, prototype, and build ML infrastructures on GCP.
Develop custom models and utilize existing Google ML APIs for real‑world data problems.
Build and deploy ML pipelines using cloud‑ML services.
Provide subject‑matter expertise on ML topics to clients and internal teams.
Document technical solutions and lead solution‑design discussions.
Assist in technical pre‑sales discussions and creation of statements of work.
Expectations Customer‑Facing: Daily interactions with customers via stand‑ups, sales meetings, sprint planning, retrospectives, or demos. Travel: Up to 35% to customer sites, conferences, and events; otherwise remote work is expected.
Job Requirements
Google Professional Machine Learning Certification (within 90 days of hire).
4+ years relevant experience designing and deploying ML solutions, preferably in a technical consulting environment.
Proficiency in Python and experience with Pandas, NumPy, scikit‑learn, XGBoost, TensorFlow, or PyTorch.
Strong understanding of ML principles and experience with supervised, unsupervised, and deep learning models.
Experience with data exploration, cleaning, feature engineering, and data pipeline orchestration (Docker, Kubernetes, Kubeflow, Airflow, MLflow).
Solid knowledge of GCP services (Storage, BigQuery, Cloud Run, Vertex AI, BigQueryML).
Experience with JupyterLab and Vertex AI Workbench.
Excellent problem‑solving and consultative communication skills.
Ability to translate complex ML concepts into actionable business solutions.
Useful Qualifications
Experience with large language models, generative AI, fine‑tuning, and prompt engineering.
Specialization in NLP, computer vision, time‑series analysis, recommender systems, or reinforcement learning.
Familiarity with other GCP data products (Cloud Pub/Sub, Dataflow, Dataproc).
Experience with model serving frameworks such as FastAPI and GCP services like Cloud Run and GKE.
Company Values
Hunger
Heart
Harmony
Benefits Unlimited PTO, paid parental leave, competitive compensation with performance bonuses, paid holidays, comprehensive medical/dental/vision plans, life and disability insurance, 401(k) with employer match, and access to Google‑certified training programs and a professional development stipend.
SADA is an equal opportunity employer. We comply with federal, state, and provincial disability laws and provide reasonable accommodations for applicants and candidates with disabilities.
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Responsibilities
Implement end‑to‑end ML solutions for clients, from requirements gathering through model deployment and iterative improvement.
Recommend, prototype, and build ML infrastructures on GCP.
Develop custom models and utilize existing Google ML APIs for real‑world data problems.
Build and deploy ML pipelines using cloud‑ML services.
Provide subject‑matter expertise on ML topics to clients and internal teams.
Document technical solutions and lead solution‑design discussions.
Assist in technical pre‑sales discussions and creation of statements of work.
Expectations Customer‑Facing: Daily interactions with customers via stand‑ups, sales meetings, sprint planning, retrospectives, or demos. Travel: Up to 35% to customer sites, conferences, and events; otherwise remote work is expected.
Job Requirements
Google Professional Machine Learning Certification (within 90 days of hire).
4+ years relevant experience designing and deploying ML solutions, preferably in a technical consulting environment.
Proficiency in Python and experience with Pandas, NumPy, scikit‑learn, XGBoost, TensorFlow, or PyTorch.
Strong understanding of ML principles and experience with supervised, unsupervised, and deep learning models.
Experience with data exploration, cleaning, feature engineering, and data pipeline orchestration (Docker, Kubernetes, Kubeflow, Airflow, MLflow).
Solid knowledge of GCP services (Storage, BigQuery, Cloud Run, Vertex AI, BigQueryML).
Experience with JupyterLab and Vertex AI Workbench.
Excellent problem‑solving and consultative communication skills.
Ability to translate complex ML concepts into actionable business solutions.
Useful Qualifications
Experience with large language models, generative AI, fine‑tuning, and prompt engineering.
Specialization in NLP, computer vision, time‑series analysis, recommender systems, or reinforcement learning.
Familiarity with other GCP data products (Cloud Pub/Sub, Dataflow, Dataproc).
Experience with model serving frameworks such as FastAPI and GCP services like Cloud Run and GKE.
Company Values
Hunger
Heart
Harmony
Benefits Unlimited PTO, paid parental leave, competitive compensation with performance bonuses, paid holidays, comprehensive medical/dental/vision plans, life and disability insurance, 401(k) with employer match, and access to Google‑certified training programs and a professional development stipend.
SADA is an equal opportunity employer. We comply with federal, state, and provincial disability laws and provide reasonable accommodations for applicants and candidates with disabilities.
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