Lead Machine Learning Engineer

We are looking for a Lead Machine Learning Engineer for TechSoftX. If you are interested, please send your resume to info@techsoftxcorp.com. Candidates should apply directly. Recruitment agencies will NOT be entertained.

About TechSoftX

Description: TechSoftX is a Sydney-based Australian software company, with presence in Melbourne, Victoria and Delaware, USA. We develop products, provide consulting, training, services, support, and partner with other companies to sell their products and services. Our expertise lies in the broad areas of artificial intelligence (machine learning, data science, optimization) and cyber security (cryptography, security, privacy, blockchain).

Vision: Our vision is to lead the future of digital innovation by seamlessly integrating artificial intelligence with advanced cybersecurity solutions, ensuring that as technology evolves, trust, safety, and human-centric progress remain at its core. We want to create a safer, smarter world by pioneering intelligent technologies that protect and empower individuals, businesses, and governments.

Mission: Our mission is to develop cutting-edge AI solutions and next-generation cyber defenses that empower organizations to thrive securely in a rapidly evolving digital landscape. We are committed to innovation, ethical technology, and building a foundation of trust in every line of code we write. We want to design and deliver intelligent, resilient technologies that defend digital ecosystems and drive innovation, safeguarding the future of a connected world.
About the role
Position: Lead Machine Learning Engineer
Location: Sydney, Melbourne, Kolkata
Overview:
The Lead Machine Learning Engineer is responsible for designing, building, and deploying scalable machine learning solutions that drive business value. This role combines deep technical expertise with leadership responsibilities, guiding a team of ML engineers and data scientists, shaping architecture and best practices, and ensuring high-quality delivery of ML products across the organisation.

The ideal candidate has strong experience in ML systems engineering, cloud-native development, applied machine learning, and MLOps. They excel at collaborating with cross-functional partners—including Data Science, Product, Engineering, and DevOps—to translate business needs into reliable, performant ML solutions.

Key Responsibilities:
Technical Leadership & Architecture
Lead the end-to-end design, development, and deployment of machine learning models at scale.
Architect robust, reusable, and secure ML pipelines, including data ingestion, model training, evaluation, deployment, and monitoring.
Define the technical roadmap for machine learning systems and align it with organisational strategy.
Evaluate and recommend best-in-class tools, frameworks, and platforms for ML engineering and MLOps.
ML Engineering & Development
Build and maintain production-grade ML solutions using modern ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Develop automated CI/CD pipelines for model training, validation, and deployment.
Implement feature engineering pipelines, model versioning, model registry, and automated retraining workflows.
Ensure ML systems meet SLAs for performance, scalability, reliability, and cost optimization.
Collaboration & Stakeholder Engagement
Work closely with data scientists to industrialise prototypes into production-ready systems.
Partner with software engineers and DevOps teams to integrate ML services into broader platform architecture.
Collaborate with product managers to understand business requirements, define success metrics, and prioritise ML initiatives.
Communicate technical concepts and trade-offs clearly to stakeholders at all levels.
Team Leadership & Capability Building
Lead and mentor a high-performing team of ML engineers, fostering technical excellence and continuous learning.
Establish and promote coding standards, best practices, and documentation.
Conduct code reviews, architecture reviews, and knowledge-sharing sessions.
Support hiring efforts and contribute to developing a high-calibre ML engineering function.
Governance, Security & Compliance
Ensure ML models adhere to ethical AI principles, fairness, transparency, and risk management frameworks.
Implement best practices in model governance, observability, drift detection, and data privacy.
Collaborate with security teams to ensure ML systems meet compliance, audit, and regulatory requirements.
Required Qualifications
Education: Master’s or Ph.D. in Computer Science, Electrical Engineering, Statistics, or a related quantitative field.
Experience:
5+ years of professional experience in Machine Learning or Data Science.
2+ years in a technical leadership or senior role, leading complex ML projects.
Demonstrated experience taking at least two ML projects from conception to production and maintaining them at scale.
Technical Skills:
Expert proficiency in Python and ML libraries (e.g., scikit-learn, Pandas).
Deep expertise in at least one major deep learning framework (PyTorch or TensorFlow).
Strong background in MLOps tools and practices (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).
Proficiency with cloud computing platforms (AWS, Azure, or GCP).
Solid understanding of data structures, algorithms, and software engineering principles.
Desired Skills & Attributes
Familiarity with Big Data technologies (e.g., Spark, Hadoop).
Experience with real-time streaming and inference systems (e.g., Kafka, Flink).
Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
A proactive approach to identifying and addressing technical debt and process bottlenecks.
Specific domain experience relevant to the company's industry (e.g., NLP, Computer Vision, Recommendation Systems).
What We Offer
Competitive compensation package
Opportunities to shape scientific strategy and drive impactful innovation
Access to state-of-the-art facilities and research tools
Professional growth through conferences, research collaborations, and advanced training
Collaborative, mission-driven environment
Visa:
No visa sponsorship is available for this position.
You must be a citizen or permanent resident of the country where the job is located.