Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4366768922&distance=25.0&f_AL=true&f_TPR=r86400&f_WT=2&geoId=103644278&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&start=125 Job Description: FortifyIQ Share Show more options Data & AI Engineer (Remote) Salem, MA · 20 hours ago · Over 100 applicants No response insights available yet Remote Matches your job preferences, workplace type is Remote. Full-time Matches your job preferences, job type is Full-time. Easy Apply Save Save Data & AI Engineer (Remote) at FortifyIQ Data & AI Engineer (Remote) FortifyIQ · Salem, MA (Remote) Easy Apply Save Save Data & AI Engineer (Remote) at FortifyIQ Show more options Your profile is missing required qualifications Show match details Help me update my profile BETA Is this information helpful? Get personalized tips to stand out to hirers Find jobs where you’re a top applicant and tailor your resume with the help of AI. Try Premium for PKR0 About the job We're seeking a Data & AI Engineer to develop intelligent data pipelines and analytics solutions that power smarter decisions across silicon design, verification, and manufacturing. You'll transform engineering data into actionable insights through automation, modeling, and visualization. Responsibilities Build and maintain data pipelines to support machine learning and analytics workflows. Collect, clean, and transform large, complex datasets from engineering environments. Develop and train predictive models for yield, performance, and anomaly detection. Automate recurring data analysis tasks and integrate models into engineering processes. Collaborate with design and software teams to embed AI-driven insights into products. Create dashboards and visualization tools for reporting and decision-making. Document code, models, and processes for transparency and reproducibility. Qualifications Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Strong skills in data manipulation (Pandas, NumPy, SQL). Experience with workflow orchestration (Airflow, Spark, or similar). 3–5 years of experience in data engineering or applied AI. Bachelor's degree in Electrical Engineering, Computer Science, or related field. Preferred / Plus Familiarity with semiconductor design, verification, or manufacturing datasets. Understanding of statistical modeling and predictive maintenance. Experience with cloud environments (AWS, Azure, GCP) and version control (Git). Knowledge of MLOps principles (deployment, monitoring, CI/CD).