In the rapidly evolving landscape of AI/ML technologies, having a seasoned Senior Technical Lead or Senior Solutions Architect is crucial for driving innovation, scaling solutions, and solving complex technical challenges. If you are passionate about shaping the next-generation infrastructures for AI/ML systems, this opportunity offers you the chance to lead large-scale, high-impact projects that will influence industries across the globe.
As part of a global team, you will be responsible for designing, developing, and deploying scalable AI/ML-driven solutions that are optimized for distributed systems, high-performance requirements, and real-time data processing. Your expertise will play a key role in transforming ideas into tangible, market-leading technologies.
Job Overview: Key Responsibilities
The Senior Technical Lead or Senior Solutions Architect will be responsible for guiding the architectural direction, driving large-scale AI/ML projects, and ensuring seamless deployment and operation of AI/ML models. Below is a breakdown of the core responsibilities:
1. Lead and Execute Large-Scale AI/ML Projects
You will oversee the execution of mission-critical AI/ML projects, ensuring they align with business objectives. Your leadership will ensure that the teams deliver solutions that not only meet current requirements but are also scalable and future-proof.
2. Architect Scalable, Low-Latency Backend Systems
As a technical leader, you will be in charge of designing backend architectures optimized for AI/ML model serving, real-time data processing, and cloud integrations. These systems will be high-performing and reliable, ready to handle large-scale machine learning workloads.
3. Drive Cloud Platform Decisions and Optimization
You will guide decisions regarding cloud platform usage (AWS, GCP, or Azure), auto-scaling, serverless architecture, and resource optimization. Your expertise will ensure that all AI/ML models deployed are efficient and cost-effective.
4. Mentor Cross-Functional Teams
Your leadership will extend beyond just project delivery to fostering a collaborative engineering culture. You will mentor engineers, helping them grow technically and professionally while ensuring that best practices, such as CI/CD, TDD, and test automation, are adhered to.
5. Ensure Scalable Deployment of AI/ML Systems
Your responsibility will include ensuring the deployment of AI/ML models into production environments that are highly available, fault-tolerant, and scalable.
6. Influencing and Shaping Future-Proof Architectures
By influencing key architectural decisions, you will help shape AI/ML infrastructures that are ready for the future. Your work will directly impact how the organization scales its technology stack to accommodate an increasing amount of AI-driven use cases.
Required Qualifications and Experience
1. Extensive Experience in Software Engineering and AI/ML Systems
- 10+ years of experience in software engineering or architecture, with at least 5+ years focused on AI/ML or distributed systems projects.
- Proven success in leading teams in designing large-scale backend systems optimized for AI/ML workloads, with proficiency in microservices, event-driven systems, and API development (RESTful/GraphQL).
2. Expertise in AI/ML Deployment and Optimization
- Extensive hands-on experience deploying AI/ML models, optimizing them for production use, and working with frameworks like TensorFlow and PyTorch.
- Strong experience in real-time data processing, including integration with backend systems for AI/ML workloads.
3. Deep Understanding of Cloud Platforms
- Advanced knowledge of major cloud platforms such as AWS, GCP, and Azure.
- Expertise in auto-scaling, serverless architecture, and fault tolerance, ensuring efficient and cost-effective scaling of AI/ML workloads.
4. Leadership and Communication Skills
- Proven ability to lead cross-functional teams, providing technical guidance and ensuring that solutions align with both technical and business goals.
- Strong communication skills to manage stakeholder expectations and report progress effectively to leadership.
5. Self-Starter with a Focus on Scalability and Efficiency
- You excel at balancing short-term technical goals with long-term scalability, ensuring that systems are both robust and capable of handling future growth.
Bonus Points: Additional Skills and Expertise
1. Familiarity with MLOps
- Experience with MLFlow, Kubeflow, or other MLOps best practices that optimize the full lifecycle of machine learning models, from development to deployment.
2. Expertise in Streaming and Real-Time Data
- Knowledge of real-time data processing and streaming technologies like Apache Kafka, Flink, and Spark that support high-concurrency AI/ML workloads.
3. Natural Language Processing (NLP)
- Familiarity with NLP frameworks such as Hugging Face and spacy, adding value to AI/ML projects focused on text, speech, or conversational interfaces.
4. Open-Source Contributions and Thought Leadership
- Contributions to the open-source AI/ML community, technical blogs, or thought leadership materials showcasing your expertise in the field.
5. Knowledge of AI/ML Security and Privacy
- Experience in addressing data privacy, security, and regulatory concerns related to AI/ML deployments, particularly in industries with strict compliance requirements.
What You’ll Get: Why Join Us?
1. Competitive Salary
- We offer a best-in-class salary because we hire only the best and reward exceptional talent.
2. Proximity Talks
- Access to Proximity Talks, where you’ll meet and learn from other top-tier engineers, designers, and product managers.
3. Cutting-Edge Technology
- Engage in building state-of-the-art technologies that influence industries and customers worldwide.
About Us: Proximity
We believe in the power of collaboration, the importance of learning, and the value of continuously innovating in the world of AI/ML.
We pride ourselves on a culture that fosters creativity, challenges assumptions, and encourages growth—whether you’re a seasoned professional or just starting your journey in AI/ML technology.