Job Title: Software Engineer – Machine Learning Company Name: Aivra Health LLC Job Url: https://www.dice.com/job-detail/452c7930-d1b2-4c63-ad3c-905e436b3e7a?filters.workplaceTypes=Remote&q=software+engineer Job Description: Aivra Health LLC Easy Apply Software Engineer Remote • Posted 10 days ago • Updated 10 days ago Full Time No Travel Required Remote $90,000 - $130,000/yr Aivra Health LLC Fitment Dice Job Match Score™ Go visible to see if you are a good match. Profile Visibility: Off Go visible! Get noticed by recruiters, make the most of your job search, and unlock more dashboard widgets when you change your profile to visible. Learn more Job Details Skills Machine Learning Operations (ML Ops) Software Engineering Summary Software Engineer – Machine Learning Launch Your Career in AI-Powered Systems 📍 Position Details Location: United States (Remote, Hybrid, or On-Site options available) Employment Type: Full-Time, Salaried Experience Level: Entry-Level to Early Career (1–3 years) Visa Sponsorship: H-1B sponsorship available for qualified candidates STEM OPT: F-1 STEM OPT candidates strongly encouraged to apply Salary Range: $90K–$130K (depending on experience, skills, and location) 🚀 About the Role We're seeking a motivated early-career Software Engineer with Machine Learning expertise to join our growing team. This is an excellent opportunity for entry level candidates and professionals with 1–3 years of experience who are passionate about applying ML in real-world production environments. You'll work alongside experienced engineers and data scientists, gaining hands-on experience in building scalable ML systems while contributing to meaningful projects from day one. 💼 Key Responsibilities ML Model Development & Deployment Assist in developing and deploying machine learning models to production Build and maintain ML pipelines for data processing and model training Implement model evaluation metrics and monitoring dashboards Support A/B testing and model performance analysis Software Engineering Develop backend services and APIs using Python Write clean, well-tested code following team standards and best practices Participate in code reviews and learn from senior engineers Debug and troubleshoot production issues MLOps & Infrastructure Help build CI/CD pipelines for ML model deployment Work with Docker and Kubernetes for containerized applications Implement data validation and feature engineering workflows Use MLOps tools for experiment tracking and model versioning Learning & Collaboration Collaborate with data scientists to understand model requirements Work with cross-functional teams in an Agile environment Stay updated on emerging ML technologies and best practices Participate in team knowledge-sharing sessions and workshops 🎯 Required Qualifications Education Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, or related STEM field Master's degree is a plus but not required entry level candidates (Class of 2022–2024) are encouraged to apply Experience 1–3 years of relevant experience (internships, co-ops, academic projects, or professional work) Demonstrated experience through personal projects, GitHub repositories, or contributions to open-source Technical Skills Programming: Proficiency in Python (NumPy, Pandas, object-oriented programming) Working knowledge of SQL and relational databases Familiarity with Git and version control workflows Understanding of software development fundamentals and data structures Machine Learning: Hands-on experience with TensorFlow, PyTorch, or Scikit-learn (through coursework or projects) Understanding of ML fundamentals: regression, classification, neural networks, model evaluation Experience with data preprocessing, feature engineering, and exploratory data analysis Basic knowledge of model training, validation, and testing workflows Cloud & Tools: Basic familiarity with at least one cloud platform (AWS, Azure, or Google Cloud Platform) Exposure to Docker and containerization concepts Understanding of REST APIs and web services Experience with Jupyter Notebooks and ML development environments MLOps (Preferred but trainable): Awareness of CI/CD concepts Familiarity with MLflow, Weights & Biases, or similar experiment tracking tools Basic understanding of Kubernetes or willingness to learn ⭐ Preferred Qualifications Internship experience at a tech company or ML-focused role Academic research in machine learning or related fields Kaggle competitions or similar ML challenge participation Experience with NLP, Computer Vision, or Recommender Systems Contributions to open-source projects or active GitHub profile Familiarity with Linux/Unix environments Strong communication skills and ability to explain technical concepts Demonstrated passion for ML through side projects or continuous learning 🌟 What We Offer Compensation & Benefits Competitive salary: $90K–$130K based on experience and location Annual performance bonuses Stock options/equity (for eligible positions) Comprehensive health insurance (Medical, Dental, Vision) starting day one 401(k) retirement plan with company matching HSA/FSA options Work-Life Balance 20 days PTO plus 11 federal holidays Paid sick leave Paid parental leave Flexible work arrangements (remote/hybrid available) $500 home office setup stipend for remote employees Professional Development & Growth Mentorship program – paired with senior ML engineers $2,000 annual learning budget for courses, books, and certifications Access to O'Reilly Learning Platform, Coursera, Udemy Conference attendance opportunities (NeurIPS, ICML, PyData, etc.) Clear career progression pathway (Mid-Level Engineer within 2–3 years) Regular 1-on-1s with manager for career development Early-Career Support Structured onboarding program (first 90 days) Regular training sessions on ML best practices and tools Exposure to diverse projects and technologies Collaborative team environment that values learning Brown bag lunch sessions with industry experts Additional Perks Latest MacBook Pro or Linux workstation Premium development tools and software licenses Team social events and activities Immigration support (H-1B, sponsorship) Relocation assistance up to $5,000 (if applicable) 🛂 Immigration & Visa Information We actively support international talent: H-1B Sponsorship: Available for candidates with bachelor's degree or higher in STEM fields STEM OPT Extension: F-1 students eligible for 24-month STEM OPT extension CPT: Current students on CPT are welcome to apply for internship-to-hire pathways Sponsorship: Available for long-term employees after 1–2 years Cap-Gap Extension: Support provided for OPT to H-1B transitions All applicants must be authorized to work in the United States or be eligible for visa sponsorship 📚 What Success Looks Like First 30 Days Complete onboarding and set up development environment Understand existing ML pipelines and infrastructure Ship first small feature or bug fix Meet with team members and stakeholders First 90 Days Independently develop and deploy ML features to production Contribute to code reviews and technical discussions Complete assigned training modules Begin working on medium-sized projects First Year Own end-to-end ML features from design to deployment Mentor new team members or interns Contribute to technical documentation and best practices Present learnings at team meetings or internal tech talks 📋 Application Process Submit Application: Resume + brief cover letter or statement of interest Recruiter Screen: 20–30 minute phone call to discuss background and interests Technical Assessment: Take-home coding challenge (ML-focused, 2–3 hours) OR Live coding session (60 minutes) Technical Interviews: 2 rounds Round 1: Python coding + ML fundamentals (60 min) Round 2: System design basics + ML concepts (60 min) Behavioral Interview: Team fit and culture discussion (45 min) Offer Decision: Typically within 1 week of final interview Total Timeline: 2–3 weeks from application to offer We understand early-career candidates are still learning – we evaluate based on potential, problem-solving ability, and growth mindset, not just years of experience. 🤝 Equal Opportunity Employer We are committed to building a diverse team and creating an inclusive workplace. We encourage applications from candidates of all backgrounds, including underrepresented groups in tech. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, or any other protected characteristic. Reasonable accommodations available during the application process for candidates with disabilities. 📧 How to Apply Ready to launch your ML engineering career? We'd love to hear from you! Submit: Resume/CV Brief cover letter or statement (3–5 sentences about why you're interested) Link to GitHub profile or portfolio (optional but highly encouraged) Any relevant projects, papers, or Kaggle profiles Current visa/work authorization status [Apply Now Button] Applications reviewed on a rolling basis. Early applications encouraged! 💡 Tips for Applicants Showcase your projects: Even if you have limited work experience, strong personal or academic projects demonstrate your skills Highlight learning: We value candidates who show curiosity and continuous learning Be authentic: We want to understand your genuine interest in ML and software engineering Prepare questions: We love candidates who ask thoughtful questions about our tech stack and culture   Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.