ML Software Engineer job in Boston, MA
Are you a forward-thinking engineer with a passion for cutting-edge technology and intelligent systems? We are seeking a Machine Learning Software Engineer to join a trailblazing tech company based in Boston, MA. In this role, you’ll have the opportunity to work on high-impact projects, build scalable ML solutions, and contribute to the next generation of AI-driven applications. If you’re ready to push the boundaries of machine learning and collaborate with top-tier talent, this position is for you.
Drive Real-World AI Solutions in a Leading Tech Hub
A fast-growing technology firm in Boston, MA is hiring a Machine Learning Software Engineer to help develop, deploy, and optimize intelligent software systems. The ideal candidate will bring deep knowledge of ML algorithms, proficiency in Python or similar languages, and experience with frameworks such as TensorFlow or PyTorch. If you thrive on solving complex problems, building reliable pipelines, and transforming data into actionable insights, this is your chance to be at the forefront of AI innovation.
Key Responsibilities of the Machine Learning (ML) Software Engineer – Boston, MA
Model Development & Deployment:
Design, build, and deploy scalable machine learning models that address real-world challenges. Collaborate with data scientists and software engineers to transition models from experimentation to production environments.
Data Pipeline Engineering:
Develop and maintain robust data pipelines for data ingestion, preprocessing, and transformation. Ensure high-quality, reliable data flow from source to model, using tools like Apache Airflow, Spark, or similar.
Algorithm Optimization:
Continuously evaluate and optimize machine learning algorithms for performance, accuracy, and scalability. Implement model evaluation techniques, A/B testing, and hyperparameter tuning to improve results.
Collaborative Research & Innovation:
Work cross-functionally with product managers, research teams, and engineers to explore new ML methodologies. Stay ahead of trends in AI/ML, propose innovative solutions, and contribute to research papers or patents when applicable.
Software Engineering Best Practices:
Write clean, maintainable, and testable code while adhering to software engineering standards. Utilize version control systems like Git, follow agile development practices, and ensure code quality through unit and integration testing.
ML Infrastructure & Tooling:
Design and maintain infrastructure for model training, deployment, and monitoring. Leverage ML Ops tools (e.g., MLflow, SageMaker, or Kubeflow) to ensure reliable end-to-end workflows and reproducibility.
Model Monitoring & Maintenance:
Track model performance in production using monitoring tools. Identify data drift or degradation over time and implement retraining strategies or automated alerts as needed.
Documentation & Knowledge Sharing:
Create detailed documentation for ML models, pipelines, and engineering decisions. Share knowledge with team members through code reviews, internal talks, and mentorship opportunities.
Security & Compliance:
Ensure ML models and systems comply with relevant data privacy laws (such as GDPR or HIPAA where applicable). Implement responsible AI principles and maintain transparency and fairness in model decisions.
Continuous Learning & Development:
Invest time in upskilling through courses, conferences, and hands-on experimentation. Bring new ideas and emerging technologies into the team to foster a culture of innovation.
What the Client is Looking for in You
As a Machine Learning (ML) Software Engineer in Boston, MA, the client is seeking a technically skilled, highly motivated professional who thrives in a fast-paced and collaborative environment. You should be passionate about machine learning, software engineering best practices, and creating intelligent systems that deliver real-world impact. The ideal candidate combines deep technical knowledge with a practical mindset and the ability to work across cross-functional teams.
Strong Background in Machine Learning & AI
The client is looking for an engineer with proven expertise in developing and deploying ML models in production environments. You should have a solid understanding of supervised and unsupervised learning, deep learning architectures, and data-driven decision-making. Experience with tools like Python, TensorFlow, PyTorch, or Scikit-learn is essential.
Software Engineering Excellence
You must be an experienced software engineer who writes clean, scalable, and maintainable code. Familiarity with building APIs, integrating ML systems into broader software infrastructure, and working within agile development teams is highly valued. Strong fundamentals in data structures, algorithms, and software design patterns are expected.
Applied Problem-Solving Mindset
The ideal candidate excels at breaking down complex problems, exploring creative solutions, and applying machine learning techniques that drive measurable results. You should have experience in working with large datasets, applying model evaluation techniques, and optimizing performance in real-world scenarios.
Passion for Innovation & Continuous Learning
The client values individuals who stay current with the latest research and advances in AI and machine learning. You should be naturally curious and open to experimentation, with a track record of contributing to innovative projects and pushing technical boundaries.
Cross-Functional Collaboration
As part of a dynamic engineering team, you should be a strong communicator who can collaborate effectively with data scientists, backend engineers, and product managers. Your ability to translate business requirements into scalable ML solutions is critical to success in this role.
Results-Oriented with a Product Focus
The client is looking for someone who understands the importance of delivering models that not only perform well technically but also solve real user and business problems. Experience in deploying end-to-end ML pipelines and monitoring production performance is a plus.
Ethical and Responsible AI Practices
You should have a commitment to building responsible AI systems that prioritize fairness, transparency, and accountability. Understanding of data privacy regulations and ethical considerations in AI is highly desirable.
FAQs About the Role – Machine Learning (ML) Software Engineer – Boston, MA
1. What are the key responsibilities of the ML Software Engineer in this role?
As a Machine Learning Software Engineer, you will be responsible for designing, developing, and deploying scalable machine learning models that support real-world applications. You will collaborate with cross-functional teams to build data pipelines, optimize algorithms, monitor model performance, and ensure end-to-end delivery of intelligent solutions. The role also includes maintaining clean code, participating in code reviews, and contributing to the continuous improvement of ML infrastructure and workflows.
2. What qualifications and experience are required for this position?
The ideal candidate should have a strong foundation in computer science, statistics, and machine learning. A bachelor’s or master’s degree in Computer Science, Data Science, or a related field is required (Ph.D. preferred for research-focused roles). Proficiency in Python and experience with ML libraries such as TensorFlow, PyTorch, or Scikit-learn are essential. Hands-on experience with building and deploying ML models, working with large datasets, and using tools like SQL, Docker, or MLflow is highly valued.
3. What technical skills are essential for success in this role?
The client is looking for individuals with expertise in machine learning algorithms, data preprocessing, and model evaluation techniques. Strong coding skills, familiarity with cloud platforms (AWS, GCP, or Azure), and experience with MLOps tools and version control systems like Git are important. A deep understanding of deep learning, natural language processing, or computer vision is a plus, depending on the team’s focus area.
4. What kind of projects will I work on?
You will work on high-impact projects that involve solving complex business problems using machine learning and AI. These may include predictive analytics, recommendation engines, customer behavior modeling, or real-time anomaly detection. Projects will span from research and prototyping to full-scale deployment in production systems.
5. What challenges can I expect in this role?
You may encounter challenges related to data quality and availability, model generalization in real-world environments, performance optimization at scale, and integrating ML systems into larger software architectures. Managing model drift, ensuring compliance with data privacy regulations, and maintaining reproducibility are also key aspects of the role.
6. What is the team and work environment like?
The team is collaborative, intellectually curious, and driven by innovation. You’ll work alongside experienced data scientists, engineers, and product managers in a fast-paced, agile environment. The company values continuous learning, open communication, and a hands-on approach to solving complex problems.
7. Are there opportunities for growth and learning in this position?
Absolutely. The company encourages professional development through mentorship programs, access to conferences, internal workshops, and dedicated time for self-learning or experimentation. There’s also room to take on more responsibility, explore leadership paths, or dive deeper into research and advanced ML techniques.
What Remuneration Can You Expect from This Job?
As a Machine Learning (ML) Software Engineer in Boston, MA, you can expect a competitive compensation package reflective of your technical expertise, industry experience, and the high demand for ML talent in today’s job market. The total remuneration typically includes:
1. Base Salary
The base salary for ML Software Engineers in Boston typically ranges from $110,000 to $160,000 annually, depending on experience, specialization (e.g., NLP, computer vision), and the size and sector of the company. Senior-level engineers or those with advanced degrees may command salaries exceeding $180,000+.
2. Performance-Based Bonuses
Many employers offer annual performance bonuses tied to individual contributions, project success, and company performance. These bonuses typically range from 10% to 25% of the base salary, with top performers potentially earning even higher incentives.
3. Equity & Stock Options
For roles in tech startups or public companies, equity-based compensation is common and may include stock options, RSUs (Restricted Stock Units), or performance shares. These packages provide long-term financial benefits and a sense of ownership in the company’s success.
4. Signing Bonuses
To attract top-tier ML talent, many companies offer signing bonuses, especially for in-demand specialists. These can range from $5,000 to $25,000 depending on experience and the company’s urgency to fill the role.
5. Relocation Assistance
If you’re moving to Boston for this role, some employers may provide relocation assistance—covering moving expenses, temporary housing, or travel reimbursement—to ease your transition.
6. Benefits & Perks
As an ML Software Engineer, you can expect a robust benefits package that may include:
-
Comprehensive health, dental, and vision insurance
-
401(k) plan with company matching
-
Paid time off (PTO) and sick leave
-
Remote work flexibility or hybrid work models
-
Professional development budgets (courses, certifications, conferences)
-
Wellness stipends or mental health resources
-
Commuter benefits or transportation allowances
Total Compensation Potential
When factoring in base salary, bonuses, and equity, total annual compensation for an ML Software Engineer in Boston may range from $130,000 to $250,000 or more, depending on seniority, technical domain, and company size. Fast-growing startups or established tech companies may offer even more competitive packages to secure top-tier talent.
How to Apply
If you are a skilled and forward-thinking Machine Learning (ML) Software Engineer seeking an impactful role in a dynamic and tech-driven environment, we encourage you to apply for this exciting opportunity in Boston, MA. This position offers a chance to build intelligent systems that solve real-world problems, contribute to cutting-edge AI development, and collaborate with industry-leading experts.
To apply, please submit your updated resume along with a brief cover letter that outlines your experience in machine learning, model development, data pipeline optimization, and real-world deployment. Be sure to highlight your expertise in Python, ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), and any relevant experience in cloud platforms, MLOps tools, or domain-specific applications (e.g., NLP, CV, predictive analytics).
This role is ideal for professionals passionate about AI innovation, clean coding practices, and delivering intelligent solutions at scale. Apply today and become a driving force in shaping the future of AI as a Machine Learning Software Engineer in Boston, MA!
For more information or to explore similar opportunities, visit our Machine Learning Engineer Recruiters Page.
Tags:
Machine Learning Engineer | ML Software Developer | AI Engineer Jobs | TensorFlow | PyTorch | Scikit-learn | Data Science | Model Deployment | MLOps | Boston ML Jobs | AI Careers | Software Engineering | Predictive Analytics | Python Developer | Cloud ML Solutions